Introductory Statistics
Free Online Course • Self-Paced Learning • No Prerequisites
Welcome to Your Statistics Learning Journey!
This comprehensive course is designed to take you from statistics beginner to confident data analyst. Each module includes video-style lessons, interactive practice problems, self-check quizzes, and comprehensive study materials.
Self-Paced
Learn on your schedule. All materials available 24/7.
Interactive
Practice problems with instant feedback and detailed solutions.
Comprehensive
Study guides, quick reference cards, and worked examples.
Research-Based
Designed using evidence-based learning principles.
Course Modules
Introduction to Statistics & Data
Learn the fundamentals of statistics and data collection methods.
- What is statistics and why it matters
- Types of data (quantitative, qualitative, discrete, continuous)
- Data collection methods (surveys, experiments, observational studies)
- Data visualization and graph types
Descriptive Statistics
Master techniques for summarizing and describing data distributions.
- Measures of center (mean, median, mode)
- Measures of spread (range, IQR, variance, standard deviation)
- Distribution shapes (symmetric, skewed, outliers)
- Boxplots and five-number summary
Probability Basics
Understand probability theory and its applications in statistics.
- Introduction to probability and sample spaces
- Counting methods (factorials, permutations, combinations)
- Conditional probability and independence
- Probability distributions and expected value
Discrete Probability Distributions
Master random variables, expected values, and the binomial distribution.
- Random variables (discrete vs. continuous)
- Discrete probability distributions and expected value
- Variance and standard deviation of discrete distributions
- Binomial distribution and applications
Continuous Probability Distributions
Master the normal and uniform distributions.
- Introduction to normal distribution and Empirical Rule
- Standard normal distribution and z-scores
- Finding probabilities using the normal curve
- Normal approximation and real-world applications
- The uniform distribution and equal probability
Sampling Distributions
Learn about the Central Limit Theorem and how sample statistics behave.
- Introduction to sampling distributions
- Central Limit Theorem and sampling distribution of means
- Sampling distribution of proportions
- Standard error and applications
Confidence Intervals & Sample Size
Learn to construct confidence intervals and determine appropriate sample sizes.
- Introduction to confidence intervals and margin of error
- Confidence intervals for means (t-distribution)
- Confidence intervals for proportions
- Sample size determination for means and proportions
Hypothesis Testing
Master the logic of hypothesis testing and learn to test claims about population parameters.
- Introduction to hypothesis testing: null and alternative hypotheses
- Type I and Type II errors, statistical power
- Hypothesis tests for means (z-tests and t-tests)
- Hypothesis tests for proportions
Hypothesis Testing for Two Populations
Compare two groups using hypothesis tests for means and proportions.
- Two-sample tests for means (independent samples)
- Paired samples (matched pairs) tests
- Two-sample tests for proportions
- Choosing the right test: decision flowcharts
Analysis of Variance (ANOVA)
Compare three or more groups using ANOVA and post-hoc tests.
- Introduction to ANOVA: why not multiple t-tests?
- One-way ANOVA procedure and F-statistic
- Post-hoc tests: Tukey's HSD and Bonferroni
- ANOVA assumptions and conditions
Simple Linear Regression
Analyze relationships between two quantitative variables using regression and correlation.
- Scatter plots and correlation coefficient (r)
- Regression equation: ŷ = b₀ + b₁x
- Hypothesis testing for correlation and slope
- Confidence intervals and prediction intervals
Chi-Square Tests
Analyze categorical data using chi-square tests for goodness of fit, independence, and homogeneity.
- Goodness of fit test: does data fit expected distribution?
- Test of independence: are two variables associated?
- Test of homogeneity: comparing distributions across groups
- Choosing the right test and checking conditions
Ready to Get Started?
Begin with Module 1 and work your way through, or jump to any module that interests you. All materials are completely free!
Learning Tips
- Start with the pre-assessment to see what you already know
- Work through all lessons in order for best understanding
- Practice, practice, practice! Do all practice problems before the quiz
- Use the study guide to review before quizzes
- Take your time – understanding is more important than speed