# Tag: statistics

## confint3: 2-Sided Confidence Interval (Extended Moodle Version) templates

Exercise template for computing the 2-sided confidence interval (with extended Moodle processing) for the mean based on a random sample. Read More ›

## ttest: Interpretation of 2-Sample t Test templates

Exercise template for assessing the interpretation of a randomly-generated 2-sample t test (including significance and type of alternative). Read More ›

## tstat2: 1-Sample t-Test Statistic (Single-Choice) templates

Exercise template for computing the t-test statistic (single-choice) from given hypothesized mean and empirical mean and variance. Read More ›

## tstat: 1-Sample t-Test Statistic templates

Exercise template for computing the t-test statistic (numeric answer) from given hypothesized mean and empirical mean and variance. Read More ›

## scatterplot: Interpretation of a Scatterplot templates

Exercise template for assessing the interpretation of a randomly-generated scatterplot regarding the joint and marginal distributions. Read More ›

## relfreq: Interpretation of Relative Frequency Tables templates

Exercise template for assessing the interpretation of a table with relative frequencies where either total, row, or column frequencies are selected randomly. Read More ›

## regression: Simple Linear Regression (by Hand) templates

Exercise template for computing the prediction from a simple linear prediction by hand, based on randomly-generated marginal means/variances and correlation. Read More ›

## lm: Simple Linear Regression (with CSV Data) templates

Exercise template for conducting a simple linear regression based on a randomly-generated CSV file. Read More ›

## gaussmarkov: Knowledge Quiz Question about Gauss-Markov Assumptions templates

Exercise template for a multiple-choice knowledge quiz question about the assumptions in the Gauss-Markov theorem. Read More ›

## fourfold2: Fourfold Table (Moodle Version) templates

Exercise template for computing a fourfold table (as presented in Moodle) of joint and marginal probabilities based on three randomly-drawn conditional or marginal probabilities. Read More ›