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Statistics 2

Free Statistics 2 study guide: 9 units with summaries, key ideas, flashcards and 270 practice questions with step-by-step solutions.

Lines up with: Second college statistics course.

Units

1. UNIT 01

   Review of Inference and Sampling Distributions

   Every method in Statistics 2 rests on the same machinery: a statistic, its sampling distribution, a standard error, and the logic of intervals and tests. This unit sharpens that toolkit before you apply it to more complex models.
2. UNIT 02

   Two-Sample Inference

   Most real questions compare two groups: a treatment and a control, two regions, before and after. This unit shows how to pick the right two-sample method and how to compute and interpret intervals and tests for differences in means and proportions.
3. UNIT 03

   Chi-Square Tests

   Chi-square tests handle categorical data: whether counts fit a model, and whether two categorical variables are related. You will compute expected counts, the χ² statistic and its df, and explain which cells drive the result.
4. UNIT 04

   One-Way ANOVA

   One-way ANOVA compares the means of three or more groups with a single F test, avoiding the false positives of many t tests. You will build the ANOVA table, interpret F, check conditions and follow up with multiple comparisons.
5. UNIT 05

   Simple Linear Regression Inference

   Regression inference asks whether a straight-line relationship seen in a sample reflects a real relationship in the population, and how precisely we can estimate it. You will test and estimate slopes, read regression output, check conditions, and build confidence and prediction intervals.
6. UNIT 06

   Multiple Regression

   Multiple regression models a response with several predictors at once, letting you estimate the effect of one variable while holding others fixed. You will interpret coefficients, run overall and individual tests, compare models and spot multicollinearity.
7. UNIT 07

   Logistic Regression Basics

   When the response is yes/no, logistic regression models the probability of 'yes' through the log-odds. You will move between probability, odds and log-odds, interpret coefficients as odds ratios, and test whether predictors matter.
8. UNIT 08

   Nonparametric Tests

   Nonparametric methods replace data values with signs or ranks so that inference does not depend on normality. You will match each rank test to its classical counterpart, compute the test statistics, and interpret results carefully.
9. UNIT 09

   Experimental Design and Two-Way ANOVA

   Good design decides what a study can conclude. This unit covers the principles of experiments, blocking, factorial designs with interactions, and the two-way ANOVA used to analyze them.