This course aims to introduce students to the fundamental concepts of introductory statistics. By the end of the course, learners will be able to understand and apply various statistical methods such as probability formulas, hypothesis testing, and different probability distributions. The course covers topics including data analysis, probability, hypothesis testing, and correlation. The teaching method involves a combination of theoretical explanations, practical examples, and problem-solving exercises. This course is designed for individuals who are interested in gaining a foundational understanding of statistics and its applications.
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
