MODULE 1: Random Variables and Probability Distributions

MODULE 2: Mean and Variance of Discrete Random Variable

MODULE 3: The Normal Distribution

MODULE 4: Random Sampling, Parameter and Statistic, and Sampling Distribution of Statistics

MODULE 5: Finding the Mean and the Variance of the Sampling Distribution of the Sample Means

MODULE 6: Central Limit Theorem

MODULE 7: Percentiles and T-distribution

MODULE 8: Length of Confidence Interval and Appropriate Sample Size

MODULE 1: Testing Hypothesis

MODULE 2: Identifying Parameters for Testing in Given Real-Life Problems

MODULE 3: Formulating Appropriate Null and Alternative Hypotheses on a Population Mean

MODULE 4: Identifying Appropriate Test Statistics Involving Population Mean

MODULE 5: Identifying Appropriate Region for a Given Level of Significance 

MODULE 6: Computing Test Statistic on Population Mean

MODULE 7: Drawing Conclusion About Population Mean Based on Test Statistic Value and Critical Region

MODULE 8: Solving Problems Involving Test of Hypothesis on Population Mean

MODULE 9: Formulating Appropriate Null and Alternative Hypotheses on a Population Proportion

MODULE 10: Identifying Appropriate Test Statistic Involving Population Proportion

MODULE 11: Identifying Appropriate Rejection Region Involving Population Proportion

MODULE 12: Computing Test Statistic Value Involving Population Proportion

MODULE 13: Drawing Conclusions About Population Proportion Based on Test Statistic Value and Rejection Region

MODULE 14: Solving Problems Involving Test of Hypothesis on Population Proportion

MODULE 15: Illustrating the Nature of Bivariate Data

MODULE 16: Constructing a Scatter Plot

MODULE 17: Describing the Shape (Form), Trend (Direction), and Variation ( Strength) Based on a Scatter Plot

MODULE 18: Calculating the Pearson’s Sample Correlation Coefficient

MODULE 19: Solving Problems Involving Correlation Analysis

MODULE 20: Identifying Dependent and Independent Variables