- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 17m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - ExcelBonus23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - ExcelBonus28m
- Confidence Intervals for Population Means - ExcelBonus25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - ExcelBonus12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - ExcelBonus9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - ExcelBonus21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - ExcelBonus12m
- Two Variances and F Distribution29m
- Two Variances - Graphing CalculatorBonus16m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - ExcelBonus8m
- Finding Residuals and Creating Residual Plots - ExcelBonus11m
- Inferences for Slope31m
- Enabling Data Analysis ToolpakBonus1m
- Regression Readout of the Data Analysis Toolpak - ExcelBonus21m
- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression15m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 29m
Intro to Collecting Data: Videos & Practice Problems
Intro to Collecting Data focuses on choosing between an observational study and an experiment based on the question being asked. An observational study collects information about the current state of things without changing anything. It is used when the goal is to describe opinions, behaviors, or conditions as they already exist, such as learning how people currently feel or what they currently report.
An experiment is used when a researcher wants to see whether a change affects an outcome. In an experiment, a treatment or change is applied to one group and compared with a group that does not receive that change. This distinction matters because experiments can support causation, while observational studies can only show what is observed and cannot establish cause. A key idea in collecting data is matching the study design to the goal: use observation to measure the current state, and use experimentation to test whether a change leads to a result.
Introduction to Collecting Data

A regional store manager wants to test whether increasing store hours increases profits, so they randomly select half of their locations to stay open an extra hour later in the evenings and compare profits between stores at the end of the month. They notice that stores open later saw higher profits on average. Is this an experiment or an observational study? Can they determine the extra hours caused the increase in sales?
Observational study; no
Experiment; yes
Observational study; yes
Experiment; no
A store surveys its target demographic and learns that 86% of people would purchase the product they’ve been heavily advertising. Is this an experiment or an observational study? Can they conclude their current advertising strategy caused the high percentage of interest?
Experiment; yes
Experiment; no
Observational study; yes
Observational study; no
An office manager wants to determine how employees feel about their personal growth and professional achievement in the last quarter. Should they run an observational study or experiment?
Experiment
Observational study
Neither
Both
A software development company created a new app for fitness, and they want to determine if using the app can lead to weight loss and increased strength in customers. Should they run an observational study or experiment?
Observational study
Experiment
Survey
Case study