Dive into a comprehensive 9-hour course on introductory statistics. Learn essential concepts including vocabulary, data sampling, probability formulas, distributions, hypothesis testing, and more. Master statistical techniques such as creating frequency tables, histograms, and box plots. Explore various probability distributions, including binomial, Poisson, uniform, and normal. Gain proficiency in applying the Central Limit Theorem, conducting confidence interval calculations, and performing hypothesis tests for proportions, means, variances, and correlations. Develop skills in analyzing contingency tables, constructing tree diagrams, and understanding Bayes' Theorem. By the end of this course, acquire a solid foundation in statistical analysis applicable to various fields of study.
Overview
Syllabus
1.1 Vocabulary and Frequency Tables.
1.2 Data and Types of Sampling.
1.3 Histograms and Box Plots.
1.4 Measures of Center and Spread.
2.1 Probability Formulas.
2.2 Contingency Tables.
2.3 Tree Diagrams and Bayes Theorem.
2.4 Discrete Probabilty Distributions.
2.5 Binomial Distribution.
2.6 Poisson Distribution.
2.7 Continuous Probability Distributions and the Uniform Distribution.
2.8 Normal Distribution.
3.1 Central Limit Theorem.
3.2 Confidence Interval for a Proportion.
3.3 Hypothesis Testing for a Single Proportion.
3.4 Hypothesis Testing for Two Proportions.
3.5 Confidence Interval for a Mean.
3.6 Hypothesis Testing with a Mean.
3.8 Hypothesis Testing for Matched Pairs.
3.7 Hypothesis Test for Two Means.
4.1 Hypothesis Testing for Goodness of Fit.
4.2 Hypothesis Testing for Independence.
4.3 Hypothesis Testing a Single Variance.
4.4 Hypothesis Testing for Two Variances.
4.5 Hypothesis Test for Several Means.
4.6 Hypothesis Testing for Correlation and Regression.
Taught by
Tyler Wallace
