An Introduction to Analyzing Statistical Data
This chapter familiarizes students with data analysis. Related topics covered are classifying variables, measures of central tendency, and measures of spread.
Visualizations of Data
This chapter covers the many ways in which data can be displayed using histograms and frequency distributions.
An Introduction to Probability
This chapter introduces the student to the basic concepts of probability, including sample spaces and events, the additive and multiplicative rules, and permutations and combinations.
Discrete Probability Distribution
This chapter focuses on introducing students to probability distributions by covering random variables, discrete and continuous variables, and binomial and geometric distributions.
This chapter expands upon the previous lesson by covering the characteristics of standard normal probability distributions and some of their applications. The chapter considers the Empirical Rule, density curves, and utilizing real world data.
Planning and Conducting an Experiment or Study
This chapter covers in further detail the process of collecting data through studies and experiments. Topics considered are bias, experimental design, and randomization.
Sampling Distributions and Estimations
This chapter deals with survey analysis by considering probability samplings, confidence intervals, and the Central Limit theorem.
This chapter deals with hypothesis testing for proportions and means, the Student's t-distribution, and two sample hypothesis testing.
Regression and Correlation
This chapter allows students to use correlation and regression coefficients in order to determine linear relationships between bivariate data.
This chapter introduces students to variance and the two Chi-Square tests: the Goodness-of-Fit test and the Test for Independence.
Analysis of Variance and the F-Distribution
This chapter expands upon the previous lesson’s introduction to variance, focusing on examining the f-max test and one- and two-way ANOVA tests.
This chapter concludes the course by introducing a series of tests that are utilized in non-parametric situations, including: the sign test, rank sum test, Kruskal Wallis test, runs test, and sign rank test.