Student-Developed Shiny Applications for Teaching Statistics

Figures & data

Fig. 1 The Measures of Association app showing an example of a Prerequisites section.

Fig. 2 Examples of simulation-based exploration modules showing the Law of Large Numbers, Confidence Intervals for Proportions, and Time Series Decompositions apps.

Fig. 3 Examples of game-based quizzing styles in the Shiny app collection showing Variable Types, Correlation Guessing, Measures of Association, and Hypothesis Testing apps.

Fig. 4 The proportion of correct answers to multiple choice assessment questions for sections using an app (in black) and sections not using an app (in red). Lines indicate 95% confidence intervals based on the logistic model.

Table 1 Confidence Intervals and p-values for increased odds of correct responses with use of Shiny apps.

Lab #	Shiny App topic	95% Confidence interval for increased odds of correct per question with app*	P-value for null of no difference
7	Law of Large Numbers	(1.65, 7.96)	0.0015
9	Confidence Intervals for Proportions	(0.80, 3.81)	0.17
10	Hypothesis Testing (Quiz Game)	(0.81, 4.27)	0.15
11	Hypothesis Testing Caveats	(1.14, 6.90)	0.03
All apps combined		(1.62, 3.56)	0.00001

* Based on ordinal logistic model for Labs 7, 9, & 11; simple logistic model for Lab 10

Table

Chapter	Topic List
Introductory apps
Chapter 1: Data Gathering	Bias and Reliability Mouse Experiment on Random Assignment Question Wording Bias Variable Types Matching Game
Chapter 2: Data Description	Correlation Guessing Descriptive Statistics Effect of Outliers Location and Variation Measures of Association (categorical) Regression Lines
Chapter 3: Basic Probability	Central Limit Theorem Law of Large Numbers Tree Diagrams Venn Diagrams
Chapter 4: Statistical Inference	Hypothesis Testing Hypothesis Testing Game Inference for Means Inference for Proportions Significance Testing Caveats Simpson’s Paradox Testing and CI Relationship Waiter Experiment
Upper division apps
Chapter 5: Probability	Bayes’ Theorem Matching Distribution Probability Applications
Chapter 6: Regression	Overfitting QQ Plot Regression Assumptions Variable Selection Variance Inflation Factor (VIF) & Collinearity
Chapter 7: ANOVA	ANOVA Models Assumptions of ANOVA ANCOVA Models Hasse Diagrams One-Way ANOVA
Chapter 8: Time Series	Time Series Decomposition Time Series Models
Chapter 9: Sampling	Sampling Methods Weight Adjustment in Surveys
Chapter 10: Categorical Data	Chi-Square Goodness of Fit Test Chi-Square Independence Test Logistic Regression Odds Ratio
Chapter 11: Data Science	Data Visualization Data Wrangling Log Transformations
Chapter 12: Stochastic Processes	Homogeneous Poisson Process Nonhomogeneous Poisson Process
Statistical issues in other disciplines
Chapter 13: Biology	Life Tables Population Growth