A New Era of Learning: Considerations for ChatGPT as a Tool to Enhance Statistics and Data Science Education

Figures & data

Table 1 Example prompts provided to ChatGPT and resulting responses generated regarding the definition of a confidence interval.

Prompt	ChatGPT response
Give the definition of a confidence interval	A confidence interval is a range of values calculated from a sample of data that is used to estimate an unknown population parameter. The interval is derived from the sample mean and a measure of variability, such as the standard deviation or standard error, and is expressed as a range of values that has a specified level of confidence associated with it. For example, if a 95% confidence interval is calculated for a population mean, it means that if we were to repeatedly sample the population and calculate a 95% confidence interval for each sample, we would expect 95% of those intervals to contain the true population mean. The width of the confidence interval is determined by the sample size, the variability of the data, and the desired level of confidence. In general, as the sample size increases or the level of confidence increases, the width of the interval will decrease.
Give the definition of a confidence interval using non-technical language	A confidence interval is an estimate of the range of values that are likely to contain a certain statistic about a population, based on a sample of that population. It’s like making an educated guess about what the true value of that statistic might be for the entire population, based on the data that we have. Think of it this way: imagine you want to know the average height of people in a certain city. You can’t measure the height of everyone in the city, so instead you measure the height of a smaller group of people, which is your sample. From that sample, you calculate a range of values that is likely to contain the average height of the entire city, and that range is your confidence interval. The level of confidence associated with a confidence interval represents the likelihood that the true value of the population statistic is contained within the interval. For example, if a confidence interval has a 95% level of confidence, that means that if you were to repeat this process many times, 95% of the intervals you calculate would contain the true value of the population statistic.
Give a response to the homework question, what is the definition of a confidence interval	A confidence interval is a range of values calculated from a sample of data that is used to estimate an unknown population parameter. It provides an interval of values that is believed to contain the true population parameter with a specified level of confidence. The level of confidence is expressed as a probability, usually expressed as a percentage, that the interval calculated from the sample data will contain the true population parameter. Confidence intervals take into account both the sample size and the variability of the data in the sample, and help to provide a measure of the uncertainty associated with the estimate of the population parameter.

Table 2 Example prompts provided to ChatGPT and resulting responses generated regarding the definition of a p-value.

Prompt	ChatGPT Response
Give the definition of a p-value	A p-value is a statistical measure that represents the probability of obtaining a result as extreme as, or more extreme than, the observed result, under the assumption that the null hypothesis is true. The null hypothesis is a statement about a population parameter, such as the mean or proportion, that we want to test using a sample of data. The p-value is calculated by comparing the observed test statistic, which measures the difference between the sample and the null hypothesis, to the distribution of the test statistic under the null hypothesis. If the p-value is small (typically less than 0.05), it suggests that the observed result is unlikely to occur by chance if the null hypothesis is true, and we reject the null hypothesis in favor of an alternative hypothesis. On the other hand, if the p-value is large (greater than 0.05), it suggests that the observed result is consistent with the null hypothesis, and we fail to reject the null hypothesis. In other words, the p-value provides a measure of the strength of evidence against the null hypothesis and helps us make decisions about whether to accept or reject the null hypothesis.
Give the definition of a p-value using non-technical language	A p-value is a number that tells you how likely it is that your research finding happened by chance. It’s like a measure of how surprising your results are. When you do a statistical test, you compare your actual results to what you’d expect if there was no effect or difference between groups. If your p-value is small (less than 0.05), it means that your results are unlikely to have occurred by chance and there may be a real effect or difference. If your p-value is large (greater than 0.05), it means that your results could have happened by chance, and there may not be a real effect or difference. So, a p-value helps you decide whether to accept or reject your research hypothesis.
Give a short definition of a p-value	A p-value is a measure of the probability of obtaining a result at least as extreme as the one observed, assuming that the null hypothesis is true.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.