Implementing a Senior Statistics Practicum: Lessons and Feedback from Multiple Offerings

Abstract

A Statistics Practicum course is offered as another option besides an internship or research experience for students to fulfill a required statistics major capstone experience. This article discusses the first and fourth offering of this practicum course, which provides a unique perspective on the initial implementation of the course and its development over time. The course offers students opportunities to carry out statistical consulting projects with external clients. Students were given multiple reflection assignments throughout the course. Challenges of the projects were discussed in the reflections, which included issues of data cleaning and analysis. Students also responded to both Likert-scale and open-ended questions on an end of semester survey. These responses provided information on sentiment regarding the consulting projects and perceived usefulness of various components of the Statistics Practicum course. Both student reflection assignments and survey responses were analyzed in this study. Explanations of the thought processes that went into setting up and running the course are included. Advice and suggestions for course improvements and successful administration are also presented.

Keywords:

• Capstone
• Senior seminar
• Statistical consulting
• Statistics Practicum

1 Introduction

Capstone courses have become ubiquitous in statistics education and serve as a beneficial pedagogical tool. Students gain exposure to real life applications of statistics, expand their statistical knowledge, and develop numerous skills. All statistics majors at the university where this study took place are required to complete a capstone experience. In the past, this has taken the form of a statistics internship or research project. With a growing number of statistics majors, many who have a second major, the practicum course was added as another option for students to satisfy the capstone requirement. Students with multiple majors may have trouble finding time to complete a statistics internship, especially if they pursue an internship for their other major. Also, occasionally internships are unpaid, which can be a financial hardship to students, as tuition money is needed to complete internship credits. The practicum course alleviates this concern while providing students a high-quality experience. Offering this course requires extensive time and energy from at least one faculty member. However, having this class available can decrease the workload for other faculty members because students enrolled in the practicum would not need a faculty member to advise an internship or research experience.

Numerous recommendations in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College report (Carver et al. 2016) are supported by the consulting-based projects completed for this course where students work in groups under the direction of a faculty member. The specific GAISE recommendations which are addressed in the Statistics Practicum course include 3, 4, and 5, which are to “Integrate real data with a context and purpose,” “Foster active learning,” and “Use technology to explore concepts and analyze data.” Whereas the term “consulting” has been used for many years, the phrase “statistical collaboration” is becoming more popular (Vance and Smith 2019). Vance (2015) defines consulting as “working cooperatively with clients to answer statistics or data questions.” In Love et al. (2017), statistical collaboration is stated as the process of “working cooperatively with domain experts to create solutions to research, business, and policy changes and achieve research, business, and policy goals.” While we use the term “consulting” throughout this article, we recognize that in many cases the projects carried out by students are also considered statistical collaborations.

The American Statistical Association’s (ASA) Curriculum Guidelines for Undergraduate Programs in Statistical Science (ASA 2014) are also addressed in multiple ways through the Statistics Practicum course discussed in this article. Three of the four key points mentioned in these guidelines are the increased importance of data science, real applications, and the ability to communicate. The data science category includes managing complex data using statistical software and advanced programming skills, which is a component of the capstone course. Additionally, due to the nature of the practicum course, real data are always utilized, and students gain practice communicating with team members and their client. The guidelines for programs in statistical science encourage capstone courses, like the Statistics Practicum, as one way that statistics students can gain experience carrying out the roles of a statistician.

Horton (2015) notes that “Statistics is a science without a practicum” (p. 142). The field of statistics is unlike traditional science disciplines which often have labs associated with them where students collaborate with classmates to solve problems and apply knowledge from class. However, students cooperating as a team to examine data, conduct analyses, and make conclusions often does occur in statistics courses. The difference is that this usually does not happen in a separately designated statistics lab course taken in conjunction with an associated lecture or non-lab course. Also, group assignments in a typical classroom setting do not serve a client. Consulting projects challenge students with real life problems to identify and solve. Horton, Baumer, and Wickham (2015) stress that statistics students need outlets to work with thought-provoking and complicated datasets of different sizes. The Statistics Practicum course is designed to be a mode for students to use the statistical and computing skills they have gained while simultaneously working with large real-world messy data. The project data could be in a format that students are not accustomed to utilizing in a classroom setting. Also, as is true in some statistical consulting settings, students may have to extend their knowledge to meet the goals of their client.

The institution where the Statistics Practicum course was offered has slightly more than 6000 undergraduate students. There are roughly 60 students pursuing a statistics major and another 60 working toward a statistics minor. It is typical for other upper level statistics courses at this institution to have between 25 and 30 students. However, the practicum course is only available to senior statistics majors. Additionally, students who pursue an internship or research experience to fulfill their statistics capstone requirement would not need to take the practicum course. Therefore, with the current number of declared majors, enrollment in this course is anticipated to be lower than most other upper level statistics courses.

The Statistics Practicum, like most courses at the institution where the class was offered, is four credits. The faculty instructor leading the practicum course serves as a mentor to students, offering guidance and support for the length of the project. The instructor is also responsible for locating organizations or companies that could benefit from statistical work completed by students in the class. It is important to find projects that are challenging and can be completed within the allotted time. The projects must also be appropriate based on the statistical and computing skills of the enrolled students. Besides being a senior statistics major, prerequisites for the Statistics Practicum course include taking a class in either R or SAS or completing the Computer Science II course. All statistics majors will have had some exposure to SAS or R in most of their previous statistics classes. It is likely that students enrolling in the practicum course would also have completed a course on experimental design and another related to regression.

The statistics education literature related to statistics practicum courses does not often take into account student feedback, especially student perceptions in multiple forms (survey results and reflection information). Of the articles we have located, there is very limited representation of student sentiment. Therefore, this article seeks to fill this gap in the literature and provide new insight into offering a successful practicum course experience. This is a useful addition to the literature in a time when undergraduate statistics curricula have seen a rise in statistical consulting offerings.

Section 2 of this article provides a literature review related to capstone or practicum experiences in statistics curricula along with associated benefits. Information on the Statistics Practicum course is presented in Section 3. Methodology information associated with this research is discussed in Section 4. Study results which include student survey findings, information on student reflection assignments, and feedback from clients are provided in Section 5. Discussion and recommendations for course administration are given in Section 6. The article ends with Section 7, which summarizes conclusions made about the Statistics Practicum Course and the associated research study.

2 Literature Review

2.1 Capstone or Practicum Experiences in Statistics Programs

A capstone experience can be described as “a long-term, multilayered project that culminates a student’s academic experience” (Martonosi and Williams 2016, p. 127). This type of experience can be fulfilled through various modes including an internship, research project, or capstone course. Throughout a statistics internship, students gain real-world experience working as a statistician or data scientist. Research experiences allow students to be mentored by a faculty member individually or in a small group to pursue statistical research, which may involve writing computer simulations or working on an open-ended data analysis problem. The focus of this article is a “Statistics Practicum” course for senior statistics majors, although the terms “capstone” and “practicum” are used interchangeably. Regardless of the type of capstone experience, it should allow for the integration of knowledge from numerous courses and provide a chance for collaboration, whether that be with a faculty member, client, or fellow students. Often a statistics capstone experience will incorporate the application of statistics or data science to another discipline.

There is a rising demand for statisticians and data science professionals, and it is increasingly important for statistics curricula to include capstone courses in which students are exposed to big data (Wasserstein 2015). Capstone courses typically involve small groups of students completing one or more projects while under the mentorship of a faculty member for the duration of a semester. Statistics practicum courses often include an applied component, which usually consists of some type of statistical consulting experience. In a statistical consulting project, students work with a client to fulfill the goals and objectives of the client. Since the Statistics Practicum course discussed in this article includes a semester-long consulting-based project under the mentorship of a faculty member, this course is considered a capstone experience.

There are a variety of designs for the implementation of statistics practicum courses. The Statistics Practicum course presented in this study was a combination of the “standalone capstone project” and “statistical consultancy” as discussed and explained by Martonosi and Williams (2016). This is because the capstone project carried out in the practicum course included both consulting practices, as well as an integral component of standalone capstone projects, which is working with the client from the beginning of a project until completion. Other types of practicum course designs mentioned by Martonosi and Williams include a project within a statistical methodology course and an instructional capstone course (no client aspect). Martonosi and Williams (2016) noted “What is common to these different types of capstones is that they help students grow as practitioners through their use of real data and emphasis on professional skill development” (p. 129).

Many researchers discuss statistics practicum, consulting, or capstone courses, but most do not consider student perceptions or feedback. Boomer, Rogness, and Jersky (2007) discuss courses in statistical consulting at the undergraduate level that are offered by several universities. These courses involve the use of real clients with real data. Additionally, the goals of these courses include development of professional skills in the form of computing, oral communication, and technical writing. Therefore, the courses mentioned by Boomer, Rogness, and Jersky along with other consulting-based courses discussed in the literature can be considered capstone courses. Kolaczyk, Wright, and Yajima (2021) discuss a statistics capstone course that is part of a data science masters program. They have a unique structure that has dedicated class time, along with additional meetings for discussion and labs to make the project more immersive. Other researchers also discuss their experience in developing and offering statistical consulting courses at the undergraduate level (Jersky 2002; Hooks and Malone 2012). Spurrier (2001) delineates the structure of an undergraduate capstone course that has been conducted four times with a total of 22 students. However, the course discussed by Spurrier did not involve consulting, but rather employment search, presentation skills, and other nonstatistical competencies. This allows students to hone workforce skills, but does not provide them with real world experience. Sanft and Ziegler-Graham (2018) provide logistical information on an academic civic engagement practicum that enables students to work with community organizations for a good cause while maintaining the traditional structure of a project based consulting class.

Bilgin and Petocz (2013) assessed feedback from twelve students taking a statistical consulting course by analyzing student reflection assignments. In these reflections, students addressed the contributions they made to their project, difficulties that arose during the consulting experience, and the advice they would give to others pursuing statistical consulting. The projects carried out were obtained from doctoral students and professors. The three main themes that Bilgin and Petocz found while analyzing the student reflection assignments were the importance of communication, learning new things, and building confidence as a professional statistician. Themes specific to motivation and engagement were examined by Bilgin, Newbery, and Petocz (2015) in reflections submitted by students enrolled in a statistical consulting course.

Kim, Alberts, and Thatcher (2014) provide details of a Center for Applied Statistics and Evaluation where undergraduate students pursue statistical consulting projects. While this can be considered a practicum experience, it is not in the form of a course, and students involved in the consulting projects are from different majors. Legler et al. (2010) describe an interdisciplinary undergraduate research program that exposes students to real life statistics work in various fields. The projects apply statistics to other areas, such as biology, and show how statistics can be used in different disciplines.

2.2 Benefits of a Statistics Capstone or Practicum Experience

The implementation of a capstone course that offers real-world experience to statistics students is recommended by numerous researchers. As explained by Martonosi and Williams (2016), it is important for statistics students to have the opportunity to use knowledge from the classroom in a professional and real-world setting. Guidance from an experienced statistics faculty member eases the transition for students into a professional setting. As part of a course that involves statistical consulting for a client, students have an opportunity to experience the entirety of skills required to carry out a consulting project, while still practicing under the guidance of a statistical expert. Also, the applied component of capstone courses allows students to learn critical skills that they may otherwise not be able to learn in a traditional course. Besides working on one or more mentored team projects, formal training related to consulting is also beneficial in a statistics capstone course. Ideally this type of instruction can be provided both by the professor teaching the course and guest speakers who have lengthy experience with statistical consulting.

Capstone courses allow for exposure to the cycle of data analysis with real-world applications (Horton 2015). This cycle can include generating appropriate questions, gathering and cleaning data, visualizing and modeling data, and effectively communicating results and conclusions. Another possible benefit of a capstone course is that students have opportunities to be exposed to new software and enhance computational skills. Capstone projects in statistics also provide students with exposure to “wrangling data,” which is the practice of cleaning and reorganizing raw data into a form usable for analysis (Kandel et al. 2011). The evolution of undergraduate statistical programs has not grown in tandem with skills necessary to handle and understand big, messy data (Horton and Hardin 2015). However, a statistics practicum course can help in providing students experiences where they work with data that is large and unruly.

Another benefit of the implementation of capstone courses is the advancement of soft skills. Soft skills are a necessary part of the consulting process, and many statistical programs lack real-world practice to apply these skills. Statistical consulting experiences provide the opportunity for students to enhance skills related to the practical application of statistics (Horton and Hardin 2015; Smucker and Bailer 2015). Through the student-client relationship, students can practice an essential component of work and success in the statistics field: communication. Unlike traditional statistics course offerings, students are required to communicate with a client, with whom they must discuss expectations and report findings. Growth in student communication skills is a common outcome of statistical consulting courses, with students often realizing the significance of these skills at the conclusion of the course (Bilgin and Petocz 2013). Besides practice in communication skills, Smucker and Bailer (2015) note that a statistical consulting capstone helps to advance teamwork and critical thinking skills.

Students benefit from a statistical consulting experience by becoming more employable for the future and finding personal meaning in making a positive difference helping a client (Bilgin, Newbery, and Petocz 2015). If there is competition for jobs, having a consulting experience could be a big advantage to a job applicant. Frazier, LoFaro, and Pillers Dobler (2017) discuss how working in teams to complete a project and present results in both written and oral formats improves collaboration and communication skills, which are useful aptitudes for future employment. Also, by working on a consulting project for a client with a real-world problem, students may be more motivated by having the opportunity to have a positive impact.

While there can be difficulty in finding appropriate and well-suited clients for undergraduate statistical consulting courses, the consulting experience can have positive outcomes for not only students, but for the clients and the university as well. In some cases, clients may be unable to pay for statistical services and therefore, would not gain statistical help without the students. Also, clients may be interested in returning to work with future participants of the course, providing meaning for students who feel that their projects are on-going (Boomer, Rogness, and Jersky 2007).

Instructors of future offerings of a capstone course can benefit as well, since they may not need to spend as much time finding appropriate client partners if they are able to collaborate again with clients from past semesters. Furthermore, creation and implementation of statistical capstone courses requires effort from faculty members, but very little additional financial support, if any (Lazar, Reeves, and Franklin 2011).

3 Course Details

3.1 Precourse Considerations

A survey was administered shortly before the course began to obtain information about students’ strengths. Question items asked students to rate themselves from “Weak or no experience” to “Excellent” in several categories including writing, editing, generating computer code, communicating with others, organizing, and skill level in SAS, R, and Python. There were also open-ended questions in this precourse survey. The questions asked during the first administration of the Statistics Practicum course in 2018 can be found in Appendix 7. Similar questions were asked in the fourth course offering from 2021. Statistics faculty members met and examined the survey results to decide on group membership. One of the goals in group selection was to make sure each student group had members with different skills and strengths. Due to the challenge of finding appropriate projects to be used by students, the partnering organizations had already been determined prior to the examination of precourse survey results.

Before the semester started, students were told that they would be divided into groups for a semester-long project and they were asked if they would be willing to be a group leader. Students were informed that the responsibilities of being a leader included guiding the team in decision making and being the primary correspondent with the partnering organization. Discussions with a colleague at North Carolina State University’s Masters of Data Analytics program introduced the idea of having faculty assign group leaders. This structure was implemented in the Statistics Practicum class as well. In the first offering of the course there were two project teams, each with four students. In the fourth offering of the course there were three project teams, two with three students and one with four students. Two faculty members besides the instructor were each assigned as an informal advisor to one of the two team leaders in the first offering of the course. Informal advisors were found to be beneficial but not necessary to the success of the teams. Therefore, these advisors were not used beyond the first course offering.

3.2 Course Information

Finding partnering organizations with appropriate data analysis projects for students to work on should begin as early as possible. The process of locating collaborators often begins in the prior semester. Due to expected fluctuations in enrollment, it is advised to have more projects than may be needed prepared for use in the course. It may be feasible to delay working with a community partner if there are fewer students in the course than expected, as long as the organizations know that a final decision on project acceptance may not be made until after the course has begun. In contrast, sourcing a new partnering organization close to the start of the course could prove to be excessively challenging. Locating potential clients was completed by contacting individuals known to faculty through personal or departmental connections. Clients selected to work with student groups included government organizations, other nonprofit agencies, and for-profit companies. Therefore, projects involved both service-based and industry-based work.

Some of the topics covered in the Statistics Practicum course discussed in this article included ethics, leadership, professional advice, and the basics of statistical consulting. Several guest speakers visited throughout the course to cover various topics. Readings were also assigned. The intention was to encourage students to reflect and foster their growth. The Practicum serves as the first exposure to real life work experience for many students, so it is important to guide them in developing both personal and statistical skills while helping them to gain collaboration experience. Guest speakers and assigned readings varied by semester.

In the first course offering, one speaker discussed statistical consulting in academia, industry, and nonprofit organizations. This guest speaker was a statistics faculty member who had previous work experience outside of academia. Another guest speaker was the Director of Biostatistics and Strategic Consulting at a local contract research organization. An administrator from the university who deals with Non-Disclosure Agreements (NDAs) also visited the class to discuss the importance of NDAs. In the fourth offering of the course, another statistics faculty member visited the course to speak about creating a data workflow for reproducible results. A second guest speaker was an alumnus who had completed the Statistics Practicum course in a previous semester. This allows students to see how a peer benefited from the course and learn about what statistics work alumni may pursue.

One reading from the first course offering was a chapter titled “Statistics in the Courtroom – United States v. Kristen Gilbert” (Cobb and Gehlbach 2005). Students also read an excerpt from the book “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” (O’Neil 2016). This excerpt provided a real-life example of Simpson’s Paradox. During the fourth offering of the Practicum class, course readings included a article on data management (Wickham 2014) and another on the importance of data visualization (Unwin 2020). A chapter on communication from a statistical consulting book by Cabrera and McDougall (2002) was also assigned.

In the first course offering, students worked in pairs on a project internal to the university during the beginning of the semester when NDAs were being finalized between the university and the organizations that were working with the student groups. This gave students some practice analyzing a small portion of a large dataset and allowed the professor to see how students worked together as well as individual student strengths. Similarly, in the fourth offering of the course, the entire class worked together on a small project with an internal client during the first few weeks of the semester.

Some class time was devoted to project work. There was no set amount of time that students were mandated to work on the project, but students were required to keep track of their project hours, which is common in some industry settings. Many students in the first offering of the class did not accurately record project hours. However, in future offerings, a structured format for tracking hours was provided to students, which improved the accuracy. Students in the fourth offering of the course spent an average of about 25 hours working on their project over the course of the semester. Throughout the semester student groups submitted interim update reports and each group gave a mid-point presentation.

In the first course offering, most students were able to attend an on-site visit at the beginning of the project where they could meet the organization contacts, learn more about the goals of the project, and ask any questions they had. However, on-site visits shifted to a virtual format due to COVID-19 restrictions. In both course offerings, students rated the contributions of their group members several times via a Google Form. Also, the professor met individually with each student to provide summary results based on the feedback from their group members.

As mentioned earlier, with only some statistics majors enrolling in the practicum course, enrollment is likely to be less than other upper level statistics courses. The first offering had eight students and the fourth offering had ten students; but due to the nature of the class, this still counted as one course load for the instructor. Some project groups decided to hold weekly conference calls with their partnering organization while others chose to rely on frequent E-mail communication. Those with set meeting times tended to have a clearer understanding of project goals and found this aided in guiding progress. Each group gave a presentation to clients at the end of the semester and submitted a final report to both their organization contact and the course professor.

Students’ grades were computed slightly differently depending on the specific course offering. However, in both semesters in which the study took place, the written reports for the team project and the team presentation were each worth between twenty-five and thirty percent of the overall course grade. Attendance and class participation together accounted for ten percent of the overall grade. Assessment of individual and group participation was worth between 15 and 20% of the overall course grade. The remaining portion of the final grade was based on the project carried out by the whole class at the beginning of the semester, reflections, and miscellaneous assignments. Due to the nature of the course, exams were not given.

4 Study Methods and Data Collection

4.1 Purpose and Research Questions

The purpose of this study was to observe and analyze outcomes and student views on a statistics practicum course. The senior capstone course was designed to give students an opportunity for growth in their applied statistical skill set. Student perceptions were investigated through the assessment of feedback regarding benefits of the course, statistical and nonstatistical knowledge gained, challenges and obstacles faced, and advice for statistics majors taking the course in the future. Overall, this study sought to answer the following research questions:

1. What are students’ personal reactions to working on the Statistics Practicum project?

2. What statistical and nonstatistical knowledge did students feel they gained from the project?

3. What activities in the Statistics Practicum course were deemed most and least beneficial by the students?

4. What challenges did students face while carrying out the project?

Plentiful information about student attitudes toward the Statistics Practicum course, the consulting project they worked on, and their perceptions of these experiences are provided by the multiple reflection assignments and the end of semester survey that was administered. An additional goal of this study is to inform other statistics programs that are either considering implementing a capstone course for statistics majors or revamping an existing practicum course.

4.2 Data Collection

Approval was received from the Institutional Review Board (IRB) to collect data from students taking the first and fourth offering of the Statistics Practicum course. These students completed three reflection assignments which were assigned shortly after students began their project, during the middle of the project, and then again once the project was completed. Specific prompts from the reflection assignments can be found in Appendix 7.

Besides information from student reflections, data from an end of semester survey were also analyzed. The first question on this survey offered Likert scale responses from 1 (strongly disagree) to 6 (strongly agree) for eleven different statements. Students were asked to choose the amount of benefit they perceived was associated with more than 20 aspects of the Statistics Practicum course, such as specific assignments or lessons. Options for this portion of the survey were: No Benefit, Small Benefit, Moderate Benefit, or Large Benefit. Students were also asked several short answer or open-ended questions. All question items from the end of semester survey for the first course offering are available in Appendix 7. Question two on this survey was modified in 2021 to include class activities from the fourth offering of the course.

IRB-approved data were also collected from clients in the form of a four-question survey that was administered after projects were completed. The first question was whether their organization had benefited from the statistical consulting project carried out by the students in the Statistics Practicum, and if so, in what ways. Information was gathered on whether the client organizations would consider working with a future Statistics Practicum class, and respondents were asked to provide an explanation for their response. Another survey item asked about ways the experience could be improved for their organization or the students. The last question for the clients was related to whether or not the amount of communication with the students was sufficient throughout the project.

4.3 Participants and Student Group Formation

The eighteen student participants in the study were enrolled in the first or fourth offering of the Statistics Practicum course. All of these students were senior statistics majors, and thirteen students also had a second major such as finance, applied mathematics, computer science, or economics. One individual from each partnering organization was asked to complete a short survey after students had presented their results to the clients.

The first offering of the practicum class had three students who identified as female and five students who identified as male. During the fourth course offering there were seven students who identified as female and three students who identified as male. Students were grouped based on preexisting statistical and coding skills, project interests, and gender identification. In the case that information on student personalities is known, this may also be useful to consider when forming groups.

Research has shown that having a single group member who is different can result in that individual being stereotyped or feeling disregarded (Brown and Mistry 2006). Also, Rosser (1998) points out that if gender and race of group members are not taken into account appropriately when designing groups in STEM fields, student learning can suffer. Therefore, groups were formed with the most ideal distribution of gender as possible. During the first offering students were divided into an all-male group and a group with three females and one male. In the fourth course offering, students were divided into an all-female group, a group with two females and one male, and a group with two females and two males.

The decision of choosing team leaders was made by the instructor in consultation with other statistics faculty. In the first course offering, more males were interested in the leadership position than females based on precourse survey results. During the first offering, one female student and one male student were selected as team leaders. Two female students and one male student were selected as team leaders in the fourth course offering.

Taking student interests into account can be helpful when setting up the groups and matching them with an organization. For example, if a practicum student has a dual major in statistics and environmental science, it would be logical to partner them with the Environmental Protection Agency if that was one of the organizations available.

5 Results

5.1 End of Semester Survey Results

Table 1 shows results for the eleven Likert scale items on the end of semester survey. Note that the average score of 5.72 indicates that most students would strongly recommend the Statistics Practicum course to other statistics majors. The minimum response on all question items but one was a 4 (Somewhat Agree) or a 5 (Agree). The only item with a lower minimum score was a response of 2 (Disagree) to the statement “I plan to put this consulting project on my resume.”

Table 1 Descriptive statistics for responses to eleven end of semester survey items.

Survey Question	Mean	SD	Min	Max
I put in a lot of effort into the semester-long statistical consulting project that was completed.	5.61	0.50	5	6
I felt that the semester-long statistical consulting project was beneficial for me.	5.67	0.59	4	6
I plan to put this consulting project on my resume.	5.11	1.13	2	6
I enjoyed working with the members of my group.	5.65	0.61	4	6
I would recommend this class to other statistics majors.	5.72	0.57	4	6
I improved my coding skills through this project.	5.06	0.90	4	6
I improved my data analysis skills through this project.	5.41	0.80	4	6
I improved my public speaking skills through this project.	4.94	0.87	4	6
I improved my writing skills through this project.	5.00	0.79	4	6
I have a better idea of the statistical consulting process now compared to before I took STS 460.	5.61	0.61	4	6
I felt that the instructor helped to guide my group in the project.	5.67	0.59	4	6

NOTE: Response options ranged from 1 (strongly disagree) to 6 (strongly agree) and are based on feedback from 18 students.

Tables 2–5 provide frequencies of themes that showed up in open-ended response items on the end of the semester survey. As shown in Table 2, multiple students noted the benefit of working in a group, collaborating with a client, and gaining new coding skills. Table 3 showcases the high frequency of students in 2018 suggesting that the reflection assignments were the least beneficial part of the course, followed by reading and discussion assignments. Students in the 2021 offering of the course felt that guest presentations, American Statistical Association collaboration videos (ASA, n.d.), and blog post homework were least beneficial. The blog assignments involved students reading a statistically related blog and summarizing blog posts throughout the semester.

Table 2 Themes present in 18 responses for the survey item asking: What three things from the class were the most beneficial?

Theme	Frequency	Frequency
	in 2018	in 2021
Meetings with client/working with a client	4	1
Onsite visit/presentation	4	NA
Group project/working in a group	4	5
Skype/video meetings	3	0
Guest speaker	2	1
New software/coding	2	2
In class work time	1	3
Interim presentation	1	1
Introductory project before main project	0	2
Writing a statistical report	0	2

Table 3 Themes present in 18 responses for the survey item asking: What three things from the class were the least beneficial?

Theme	Frequency	Frequency
	in 2018	in 2021
Reflection assignments	6	1
Reading assignments and discussions	4	0
Marshmallow challenge	3	NA
Time fillers – more time wanted for project	2	0
Multiple presentation practice/ midterm presentation	2	1
In-class lectures/training	2	2
NDA	1	0
Guest presentations	1	4
Introductory project before main project	1	2
Blog journals	NA	4
ASA consulting/collaboration videos	NA	4

When students were asked about the usefulness of the course, most students noted the benefit of having an applied real-world experience. Some of the themes in student responses to the question on whether it was useful to take the Statistics Practicum course can be observed in Table 4. There were multiple students that stated more than one reason why the experience was beneficial.

Table 4 Themes present in 18 responses for the survey item asking: Overall do you think it was useful for you to take the statistics practicum course? Please explain your response.

Theme	Frequency	Frequency
	in 2018	in 2021
Yes, gained consulting/applied/real-world experience	5	5
Yes, communication skills improved	3	1
Yes, obtained new/improved skills	2	2
Yes, the experience looks good for employers and/or graduate school	1	2
Yes, class allowed creativity	1	0
Yes, the course gave me an idea of what working in the real world could be life	0	1
No, only because I do not intend to go into a statistics-related job.	1	1

As shown in Table 5, 14 out of 18 students responded that they would have rather completed the statistics consulting project with an outside organization as opposed to an internal client from within the university. One student noted that working with an external collaborator felt much more like a client-consulting relationship compared to a student-faculty or student-staff relationship, which would have been the case with an internal client. Another student stated “With an outside organization, there is an expectation of quality and no excuses.” The student that preferred to work with an internal client stated that an outside client with an analytics team would likely value the work less than an internal client, and regular communication would be easier with an on-campus client. Two students did not have an opinion on the type of client, and the student that preferred both internal and external clients be available wrote that an internal client could be better for students interested in graduate school while an external client might be better for students wanting to go into industry.

Table 5 Themes present in 18 responses for the survey item asking: Based on what you know now, do you think you would have rather completed this senior statistics consulting project with an outside organization as the client or with an internal client from within the university? Please explain your response.

Theme	Frequency	Frequency
	in 2018	in 2021
Outside client preferred	6	8
Internal client preferred	1	0
No Opinion/Allow both outside and internal clients	1	2

5.2 Results from Reflection Assignments

In the second reflection assignment, students were asked to discuss ways that the project had changed and/or improved from the initial plan. Participants wrote that they were able to modify the initial design of their projects after receiving advice from the client. Many of the participants reported removing plans for a statistical model after receiving feedback. Client input helped students to better understand which variables were more important to focus on. Visualization of data and the use of Tableau was another aspect of the project that was not foreseen to be used/needed as heavily as it was during the project. Several students mentioned improvements to their analysis approach with respect to variable formatting, new software usage, text analysis improvements, and a shift in focus regarding specific variables in the data.

Responses varied among participants on advice for future students taking the Statistics Practicum. One student noted the importance of being open-minded about the project, while another mentioned that consultants should have patience when working with large datasets. Another student encouraged future students to “be open to the fact that this experience will likely be significantly different than experiences in the classroom.” Multiple students stressed the importance of establishing a plan for the project, while creating and modifying goals throughout the project so tasks can be completed in a manageable time frame.

The final reflection included a prompt on whether students thought the project was beneficial or not and why. Every student noted that they felt carrying out the project was beneficial to them, at least in some way, with many stating both educational and professional skills gained from the course. Students who planned to continue their statistical endeavors postgraduation were inclined to feel that the project was more beneficial. Also, many students mentioned the acquisition of new skills, particularly soft skills. The applicative nature of the skills learned through the practicum was valued by all course participants. One student highlighted the importance of practicing statistical skills in application prior to entering the workforce: “I embraced the learning experience that this project had to offer because I would rather learn from my mistakes in a classroom setting rather than at my future job because those mistakes could have more serious impacts.”

Students realized that the process of completing the capstone project was not as defined as projects encountered in a traditional statistics course. One student wrote “this project gave me experience in real data analytics. We had to perform data manipulation and were given multiple updated datasets throughout the semester. This showed me that statistics in the real world is not going to be as structured as it is in the classroom.” Through the project, students were able to identify concrete skills that would benefit them postgraduation. These included communication, software and coding abilities, group work experience, and formal presentation practice. Two students suggested that the practicum course become available to juniors, so that these students can network during a time when they are likely looking for a summer internship.

In response to the reflection question asking what they liked about the project experience, students responded with a variety of positive responses. The most prevalent part of the course that students enjoyed was the guidance component. Both client and faculty member feedback were mentioned as significant positive factors in their experience. The group work aspect of the course was also highlighted by most students who appreciated the ability to solve problems with people who have skill sets different from their own. One student reflected by stating “I liked the group aspect of the project a lot. I thought that working in groups allowed us to bounce ideas off each other while also playing to the strengths of group members.”

There was an item in reflection two that asked about personal reactions to working with the partnership organization. Satisfaction with partnering organizations was generally positive, with some minor difficulties or obstacles, which aligned with what is seen within the typical consulting process. Half of the students stated that they “enjoyed” working with their partnering organization or found the experience “pleasant.” Conflicting responses were reported for both the client’s availability to communicate, as well as students’ reactions to working with a client with or without in-depth statistical knowledge.

Instructions from the client were sometimes unstructured. Several students did not enjoy the unstructured nature of the consulting project. When asked about project dislikes in the third reflection, many students made comments regarding a lack of specific guidelines and instructions from the client. It is typical in consulting relationships and experiences for the client to not provide specific well-defined goals or expectations (Kenett and Thyregod 2006). In contrast, some students appreciated the freedom of the consulting project, with one student noting, “I really enjoyed working with my team to problem solve and tackle a new type of project. I also liked the fact that we were trusted with so much responsibility and given the trust to take the project in several different directions.” Another student alluded to the typical nature of a consulting course when they wrote “I expected to have a project prompt with clearly laid out instructions and a clear direction of the organization’s expectations. However, I think we all gained new skills by having to create our own path and navigate a project mostly on our own.”

In the final reflection assignment, students from the first course offering were asked about whether visiting the partnering organization was a beneficial experience and why. Participants of the Statistics Practicum course provided positive responses with regards to visiting their client. All students reflected that the experience was beneficial or very beneficial. By visiting their partner organizations, students were able to meet their client and begin to build a relationship. More than half of the students noted the benefit of learning the context behind their projects. The visitation allowed many students to get questions answered and gain a better understanding of client expectations and goals. Two students reported increased clarity regarding future direction for their project from their visit with the client. As exemplified by one student, “going to the facility itself allowed us to ask more questions that weren’t specifically about the project itself but about the organization and our audience, which allowed us to better tailor our article to the organization.”

Students were asked to relay what they would do differently if they were to do this type of project again. Some students felt that they completed the projects to the best of their ability and would not have changed much about how they went about completing the consulting project. In contrast, other students expressed that they would have asked their clients questions sooner and with more frequency. Several students noted that they would have liked to have increased their involvement in the visualization or Tableau part of the project. Others wished that they had focused on different aspects of the data within their projects. A commonly noted place of improvement for the future involved the timeline of the project. These responses included discussion of actively working on the project and designing a project plan earlier in the semester.

All three reflection assignments asked questions related to difficulties or challenges faced in the project. Table 6 shows the challenges faced by the eighteen students who took the Statistics Practicum course during the first or fourth offerings. Frequencies are shown for each of the three reflection assignments. It can be seen that difficulties with data management, data analysis and coding were common throughout the course.

Table 6 Categories for difficulties or challenges faced in the practicum project from students in both 2018 and 2021.

Category	Frequency	Frequency	Frequency
	(Reflection 1)	(Reflection 2)	(Reflection 3)
Communication with client	3	1	0
Cleaning data, data formatting issues, missing data	6	6	5
Data analysis	5	4	5
Difficulty collaborating as a group	2	2	3
Sharing or accessing data/code	1	1	3
Keeping up with client timeline	1	1	0
Coding and software challenges	4	5	4
Getting project started	1	3	2
Challenges related to working with a large dataset	3	3	2

NOTE: Reflections 1 and 2 had 18 responses while Reflection 3 had 17 responses.

In the first reflection assignment, students were asked to report on the statistical and nonstatistical knowledge they thought they would gain from the statistical consulting project. Then in the final reflection after the project had been completed, students addressed what statistical and nonstatistical knowledge they acquired. Participants of the practicum course described the advancement of various skills, including data management and data cleaning, statistical analysis techniques, how to use a variety of statistical software, statistical consulting experience, and a deeper understanding of statistical modeling. Additionally, soft skills were frequently mentioned in student reflections. The statistical consulting experience allowed for several students to report an improved ability to relay statistical findings to a nonstatistical audience upon the conclusion of the course. Almost all students mentioned an improvement in their communication skills due to recurring opportunities to practice such skills with their client. The applied nature of the statistical capstone allowed for the growth of hard skills alongside the development of soft skills necessary for the workforce. Figure 1 provides a Venn diagram with a circle for the first and last reflection assignments. A notable trend was that data visualization was mentioned by multiple students as something they gained from their project that was not mentioned in the first reflection.

Fig. 1 Statistical and nonstatistical knowledge that students expected to gain (Reflection 1) and thought they gained (Reflection 3) from the project. Items are responses to questions regarding expected or gained knowledge; red font indicates statistical knowledge and blue font indicates nonstatistical knowledge.

5.3 Feedback from Clients

Two of the five clients responded to a survey about their experience working with the Practicum students. Both of the respondents felt that their organization had benefited from the project. One stated that the project gave the organization a more in-depth analysis of the data, while the other felt it was a great way to make a case that the project should be taken on by a full-time employee. The clients also responded affirmatively that they would work with a future Statistics Practicum course. One reason for this was that it is a great way to enhance the project without spending a lot of extra time demonstrating concepts, and the other respondent stated that it was a beneficial experience for everyone and that both the students and faculty were easy to work with.

When asked about ways the experience could be improved, both clients mentioned the challenges of the NDA process and how streamlining this process in the future would allow students more time for the project. To address whether the amount of communication with students was appropriate, one respondent stated that the weekly meetings were beneficial and allowed for a sufficient amount of communication. Another client representative, which met with the statistics students only a few times during the semester, responded that more conference calls throughout the project would have been useful.

6 Discussion and Recommendations for Course Administration

The student reflections provided valuable insight into student experiences and learning in the course, which is important information for instructors. However, most students in the first offering of the Statistics Practicum course did not think the reflection assignments were beneficial. It is possible that reflections and other smaller assignments were rated as being less helpful because students expected or wanted to have more project work time. However, reflection can help students to process what they have learned and recognize the impact and value of their newly found knowledge. Reflection allows for students to become more cognizant of their growth throughout the learning experience and “develop a sense of their own personal and professional development” (Stefani, Clarke, and Littlejohn 2000, p. 163). Reflection can also foster the development of meaning attached to their capstone learning or professional experience (Astin et al. 2000). In the fourth offering of the course, most students did not object to the reflection assignments being useful, possibly because the benefit of these assignments was relayed successfully.

Each participant provided recommendations in their reflection responses for a question regarding how the course could be improved for future offerings. Several recommendations involved the data used for the project. For example, some students wanted access to more data and datasets that were already formatted or cleaned prior to student use. However, data cleaning is part of the statistical process. This exemplifies the discrepancy between data analyzed in a traditional class and the data utilized for the Statistics Practicum course. Some students also mentioned that they would have benefited from knowing the specific analysis method to carry out with the data, but clients generally seek statistical consulting because they do not have all the answers themselves. Additionally, in many consulting projects there is not usually a direct answer. Students may be accustomed to problems in other courses which are not as vague or large-scale in scope, so the Statistics Practicum course provides a space to get accustomed to the challenges and the unstructured nature of statistical consulting.

Other themes presented in student reflections included a desire for increased and more concise communication from the client, for use of a different type of consulting client for the course (internal client or a client without an analytics team), and for a deeper understanding of the client goals and background. Students also expressed that they would have preferred if the project had started sooner. To do this, the process of generating and signing nondisclosure agreements must be completed earlier in the semester.

Students also provided advice for future students participating in the course. Patience, mental flexibility, and open-mindedness were common themes found in student reflections on advice to future course participants. Students stressed the importance of making a plan and modifying the goals of the project as needed while carrying out the project.

Instructor recommendations for a Statistics Practicum course include having NDAs ready early in the semester or before the semester begins so that students can start projects as soon as possible. NDAs in the first course offering required students to keep files related to the project on a password protected thumb drive. Initially two thumb drives were given to each group, but later each student received one since some students were not able to do individual project work without access to the data and other files. The NDA forms used in the fourth course offering were less restrictive and only required students to work on their personal computer. If students must use a lab computer and are not able to save work on that computer, providing a thumb drive to each student can be beneficial. However, it may be more convenient if students are allowed to use personal computers.

Only outside organizations were used as clients for the main projects in the two course offerings in which student data was gathered. However, in another semester in which the course was offered, internal clients were paired up with student groups for the main project. After comparing both options, it appears that the stakes are higher with an outside organization, but working with an external client is also likely to be a more similar experience to what a statistician deals with post-graduation. However, in some cases an internal client may be easier to find. Additionally, with communication over Zoom and other platforms becoming increasingly common, a successful project does not need to involve in-person communication or in-person presentations. Therefore, faculty are encouraged to consider partnering organizations that are located outside of the city, state, or location where an instructor’s home university is located.

Regardless of who the clients are, the professor should stress that the student groups frequently communicate with their client and provide regular updates. A weekly or bi-weekly meeting with the client should be encouraged. It is also essential to maintain good relationships between students and clients. If it becomes evident that a student group will be unable to complete the project based on client expectations, then students should make this clear. If this occurs, students should be encouraged to submit their progress, and in some cases a large-scale project could be carried over into a future semester for completion.

A team leader for each group was assigned by the instructor prior to students starting the main project. However, it was noted in the first offering of the course that one student who did not formally have the designation of group leader still emerged as a leader who successfully guided their group. Therefore, assigning leaders in advance may not be necessary in some cases. However, the drawback to this is that without any assignment of a group leader by either the instructor or fellow students, a group may end up leaderless and thus, lack direction related to project decisions. Therefore, we recommend that the instructor assign a leader to each group before the main projects are assigned.

Other suggestions from the instructor include offering a tutorial during the semester on Tableau, which two of five project groups ended up using in their final project along with other software. Inviting a guest speaker to talk about a specific software program is one option, but an easy alternative is for students to do an online tutorial. Student reflections throughout the project can be beneficial, but without explaining this to the students, they may think that their professor is assigning busy work when they could otherwise be working on the project. Therefore, a short discussion of the purpose of student reflections could be advantageous. If time permits, the topic of sample size calculations could be a useful addition to the course curriculum. Although this was not necessary for the projects completed by students, sample size computations are often an important part of statistical consulting.

Also, it could be valuable to carry out a role play during class in which the instructor plays the part of a company/organization representative. In this mock meeting, students would play the role of statistical consultants and must ask appropriate questions to the client to figure out what the client is looking for. This would allow students to practice communicating with a client in a low-stakes setting. Taplin (2003) advocates for the use of role-play to teach skills needed for statistical consulting and provides some evidence of its benefits. Another way to improve skills necessary for consulting is to record sessions with a client so students can review their interactions (Vance 2015).

Communication among team members was not bad, but it could be improved. For example, sometimes students did not make it clear to other group members when they would be working on the project outside of class and what parts of the project each person would be responsible for completing. Therefore, assigning readings related to teamwork and discussing how to effectively function as a team might be productive. Working efficiently as a team is a soft skill that is also valuable beyond college. Additionally, if students improved their ability to work in a team, their ability to communicate successfully during the project and meet goals could be improved.

Although having three or four students in each group worked well, a group with five students could also be successful. More students in a group may add logistical challenges, especially if the group needs to meet simultaneously outside of class. However, five members could broaden the set of skills that are contained within the group, and a group with more students might be more diverse compared to a smaller group. Having larger group sizes could also make the course more sustainable since a smaller number of overall projects would be needed.

The workload for the instructor of a Statistics Practicum course can be high, especially before the course starts when the instructor must find appropriate clients to work with. However, the benefits that the students and clients gain makes the challenge of finding clients worth the effort, and faculty are encouraged to begin their search for partnering organizations in the semester before the course is offered. Also, clients can collaborate with practicum students over multiple different classes, which makes finding clients for future offerings of the course easier. The instructor workload during the semester depends on the number of partnering organizations, which will be based on the number of enrolled students and the size of the student teams. With a class that is working with two or three partnering organizations, the workload is likely similar to a typical course. However, the scope of the consulting projects is a large factor in determining the time commitment for both the students and the instructor. If it is financially feasible, it is recommended to set the course cap at no more than fifteen to twenty students, especially if there are no additional faculty members who are aiding the course instructor in mentoring student teams.

7 Conclusion

The Statistics Practicum course offers students the ability to learn the inner workings of a consulting project, while benefiting from the guidance of a statistics faculty member. This course provides a learning environment where the risks associated with making an error are less compared to a paid work setting. This is important since making mistakes and learning how to do things more efficiently are integral parts of the consultancy learning process. Consulting courses like the one discussed in this article also allow students to learn software currently used in the statistical field (Horton 2015). Besides practice with current technologies, consulting courses also provide an opportunity for students to learn crucial soft skills needed to be a successful statistical consultant. Students from both offerings of the course noticed the importance of these skills following completion of the course. One student noted “I really appreciated the opportunity to work on a true consulting project and the soft skill development that came with that opportunity.” Due to the nature of the course, it has similarities to an internship experience and therefore, could be useful for demonstrating applicable statistical experience to future employers.

Some students realized the significance of their contributions to the client’s project. This is demonstrated in one reflection assignment where a student stated “the experience is rewarding knowing that what we did as undergraduates made an impact at the partnering organization.” Allowing students to carry out the whole process of a statistical consulting project helps them to further realize the applicability and importance of the statistics discipline to other fields.

This study was restricted by the number of participants in the course, so it was not possible to collect data from large numbers of individuals within two course offerings. Another limitation is that students submitted reflection assignments for a grade, so responses were potentially biased in order to look favorable to the professor. Future research on statistics practicum courses could benefit from collecting anonymous reflection information which is not graded. Another avenue for further research involves surveying alumni who have taken the class to get their impressions on the applicability of the class. It would be interesting to see if graduates have used skills they gained in the course for their jobs or completed similar consulting projects as part of their employment. The goal of the course is to prepare students for statistics in the real world, so alumni insight and experiences could be used to evaluate its success.

This study has shown the benefits of the Statistics Practicum Course and helped to identify areas for improvement. Overall, this capstone course enhances student learning and provides real world experiences. The consulting projects that are part of this course encourage students to challenge themselves and aid in the development of numerous skills. With thoughtful implementation, the Statistics Practicum is an immensely beneficial course.

Appendix A:

Precourse Survey

1. Please rate your skills in each of the following categories as Excellent, Very Good, Good, Not so Good, Weak or No Evidence.

   1. Writing

   2. Editing

   3. Generating computer code

   4. Editing computer code

   5. Communication with others

   6. SAS skills

   7. R skills

   8. Python skills

2. Aside from the categories in the previous table, what do you think your strongest contribution will be to the team-based practicum project? (What is your strength?)

3. Aside from the categories in the previous table, what is a characteristic that is not your strength that you hope a team member will possess? (What is your weakness?)

4. Have you used or been taught computing extensively in other courses or projects? If so, please indicate the computing languages or programs and how you have used them.

5. What is your preferred availability outside of class (weeknights, weekends, mornings, evenings, typical business hours)?

Appendix B:

Reflection Prompts

Reflection I

1. How confident do you feel that you can carry out the analysis goals of the partnering organization? Explain.

2. What difficulties/challenges do you think you will face with this project?

3. Do you think you will gain any statistical knowledge from working on this project? Explain.

4. Do you think you will gain any nonstatistical knowledge from working on this project? Explain.

5. If you were to talk to a friend about this project (assuming that hypothetically the NDA did not prevent you from doing so), what would you say to your friend?

6. Do you feel comfortable with the current state of the project? Explain why or why not.

7. Is there anything your instructor can do at this time to help you with this project?

8. For those who visited the partner organization on site, please describe your visit and provide information on who you met, what you learned, what the visit was like, whether the visit seemed useful, etc.…. If you were not able to visit your organization on site, please talk about what you learned about the visit from your group members who did attend the visit.

Reflection II

1. How confident do you feel that you can carry out the analysis goals of the partnering organization? Explain.

2. What difficulties/challenges have you faced with your project? Are there things that you have done or can do to overcome any of these difficulties/challenges? If so, explain.

3. Do you feel comfortable with the current state of the project? Explain why or why not.

4. Discuss ways that the project has changed and/or improved from the initial plan.

5. Discuss your personal reactions to working with your partnering organization.

6. Discuss your personal reactions to working on your project.

7. Is there anything your instructor can do at this time to help you with this project?

Reflection III

1. Do you feel that you have successfully completed the statistics consulting project based on the goals of the partnering organization? Please explain.

2. What difficulties/challenges did you have with your project? What did you do to overcome these difficulties/challenges?

3. What statistical knowledge or experience did you gain from this project?

4. What nonstatistical knowledge or experience did you gain from this project?

5. If you were to talk to a friend about the project that your group completed (assuming this was allowed), what would you say to your friend?

6. Discuss ways that the project changed and/or improved throughout the semester.

7. Discuss your personal reactions to working with your partnering organization.

8. Discuss your personal reactions to working on your project.

9. Was your experience with this project different than what you originally thought it would be at the beginning of the semester? If so, explain.

10. What, if anything, did you like about the project experience?

11. What, if anything, did you dislike about the project experience?

12. Do you have any recommendations on how your current instructor or another STS 460 instructor can improve this type of project for future students?

13. Is there anything that you would do differently if you were to do this type of project again? Explain.

14. Now that you have completed a capstone-type statistical consulting project, what advice would you give other students pursuing a similar type of project?

15. Was visiting your partner organization a beneficial experience? Why or why not?

16. Do you think this project was beneficial to you? Why or why not?

Appendix C:

End of Semester Inventory

1. Please rate your agreement or disagreement with the following statements from 1 (strongly disagree) to 6 (strongly agree).

   1. I put in a lot of effort into the semester-long statistical consulting project that was completed for STS 460.

   2. I felt that the semester-long statistical consulting project was beneficial for me.

   3. I plan to put this consulting project on my resume.

   4. I enjoyed working with the members of my group.

   5. I would recommend this class to other statistics majors.

   6. I improved my coding skills through this project.

   7. I improved my data analysis skills through this project.

   8. I improved my public speaking skills through this project.

   9. I improved my writing skills through this project.

   10. I have a better idea of the statistical consulting process now compared to before I took STS 460.

   11. I felt that the instructor helped to guide my group in the project.

2. For each of the parts of the STS 460 course listed below, please choose the amount of benefit you think is associated with the corresponding item. Optional responses are No Benefit, Small Benefit, Moderate Benefit, or Large Benefit.

   1. Marshmallow Challenge activity

   2. Analyzing the sustainability data at the beginning of the semester

   3. Reading and discussion questions on “Weapons of Math Destruction”

   4. Reading and discussion on “Statistics in the Courtroom” about the nurse Kristen Gilbert

   5. Guest speaker on consulting practices

   6. Guest speaker on Biostatistics and Contract Research Organizations

   7. Leadership training lesson

   8. Ethics training lesson

   9. Visiting the community partner on site at the beginning of project

   10. Preparing for and giving group presentation to the class

   11. Watching in-class presentation given by the other group

   12. Preparing for and giving online interim presentation

   13. Preparing for and giving final presentation on site

   14. In-class time to work on projects

   15. Written reflection assignments

   16. Receiving feedback from group members

   17. Working on the project in a group as opposed to individually

   18. Learning about coding or software programs available to analyze data

   19. Writing the report to give to the client

   20. Giving the final on-site presentation

   21. Having another faculty besides the instructor to discuss the project with the group

3. What 3 things from the class were the most beneficial? You may mention things from the lists above or state something that was not in the list above.

4. What 3 things from the class were the least beneficial? You may mention things from the lists above or state something that was not in the list above.

5. Overall do you think it was useful for you to take the statistics practicum course? Please explain your response.

6. Based on what you know now, do you think you would have rather completed this senior statistics consulting project with an outside organization as the client or with an internal client from within the university? Please explain your response.