STT 200

MSU

Course Overview

Lessons & Practice

I. Welcome

1. Descriptive Statistics

2. Exploratory Data Analysis

1.8hr

2.1.1. Pie Chart3 min

2.1.2. Practice

2.2.1. Bar Chart3 min

2.2.2. Practice

2.3.1. Segmented Bar Chart (or Stacked Columns)3 min

2.3.2. Practice4 min

2.4.1. Contingency Table (Two-Way Table)4 min

2.4.2. Simpson’s Paradox3 min

2.4.3. Practice

2.5.1. Histograms4 min

2.5.2. Practice2 min

2.5.3. Practice2 min

2.5.4. Practice

2.6.1. Dot Plots5 min

2.6.2. Practice

2.7.1. Frequency Polygons2 min

2.7.2. Practice4 min

2.8.1. Stemplots (Stem-and-Leaf Plots)2 min

2.8.2. Practice3 min

2.9.1. Times Series Plots2 min

2.9.2. Practice2 min

2.10.1. Measures of Central Tendency7 min

2.10.2. Mean and Median Example2 min

2.10.3. Practice

2.10.4. Practice2 min

2.10.5. Practice3 min

2.11.1. Skewness and Symmetry 6 min

2.11.2. Practice

2.12.1. Range and Interquartile Range11 min

2.12.2. Variance and Standard Deviation6 min

2.12.3. Practice3 min

2.12.4. Practice3 min

2.12.5. Practice

2.13.1. Percentiles4 min

2.13.2. Example2 min

2.13.3. Practice

2.14.1. Boxplots and Five Number Summary9 min

2.14.2. Practice4 min

2.14.3. Practice

3. Regression Modeling

1.9hr

3.1.1. Scatterplots5 min

3.1.2. Practice

3.2.1. Correlation5 min

3.2.2. Practice

3.3.1. Solving for Correlation2 min

3.3.2. Example6 min

3.3.3. Practice4 min

3.3.4. Example3 min

3.3.5. Practice

3.4.1. Coefficient of Determination (R Squared)7 min

3.4.2. Assessing Goodness of Fit6 min

3.4.3. Practice

3.5.1. Solving for the Regression Line (r, Sy, Sx Method)5 min

3.5.2. Example7 min

3.5.3. Practice (Version 1)3 min

3.5.4. Solving for the Regression Line (Least Squares Method)2 min

3.5.5. Example5 min

3.5.6. Practice (Version 2)5 min

3.6.1. Predictions3 min

3.6.2. Residuals (Errors)5 min

3.6.3. Practice

3.6.4. Residual Plots2 min

3.6.5. Regression Diagnostics 5 min

3.6.6. Practice

3.6.7. Standard Deviation of the Residuals5 min

3.6.8. Practice

3.7.1. Estimating the Coefficients of the Linear Regression Model9 min

3.7.2. Measures of Variation in Regression9 min

3.7.3. Practice

3.8.1. Standard Error and R Square Formulas7 min

3.8.2. Example5 min

3.8.3. Practice4 min

4. Foundations of Inference

1.6hr

4.1.1. Sampling Variability & Sampling Distribution12 min

4.2.1. Drawing Samples From a Finite Population8 min

4.2.2. Example4 min

4.2.3. Practice3 min

4.3.1. Introduction to Confidence Intervals14 min

4.4.1. Margin of Error and Sample Size3 min

4.4.2. Practice

4.5.1. Introduction to Hypothesis Testing 15 min

4.5.2. Hypothesis Testing Steps25 min

4.6.1. Type I and Type II Errors5 min

4.6.2. Type I and Type II Errors1 min

4.6.3. Practice

4.6.4. Practice

4.6.5. Power7 min

4.6.6. Practice

5. Statistical Inference

6hr

5.1.1. Confidence Interval for a Proportion2 min

5.1.2. Example5 min

5.1.3. Practice4 min

5.2.1. Hypothesis Test for a Proportion10 min

5.2.2. Example4 min

5.2.3. Practice5 min

5.2.4. Practice9 min

5.3.1. Confidence Interval for a Mean13 min

5.3.2. Example4 min

5.3.3. Practice3 min

5.4.1. Hypothesis Test for a Mean3 min

5.4.2. Example16 min

5.4.3. Example8 min

5.4.4. Practice4 min

5.5.1. Confidence Interval for Differences in Population Means (Pooled and Unpooled)6 min

5.5.2. Confidence Interval for Two Means Containing Zero7 min

5.5.3. Confidence Interval for Two Means (Independent Populations)9 min

5.6.1. Comparing Two Independent Means9 min

5.6.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

5.7.1. Match Pairs for Dependent Means12 min

5.8.1. Matched Pairs Confidence Interval for Differences in Two Dependent Population Means4 min

5.8.2. Practice

5.9.1. Hypothesis Test for Matched Pairs11 min

5.9.2. Example7 min

5.9.3. Practice3 min

5.10.1. Unpooled t-test (Unequal Variances)4 min

5.10.2. Example (Unpooled)11 min

5.10.3. Practice (Unpooled)5 min

5.11.1. Pooled t-test (Equal Variances)3 min

5.11.2. Example (Pooled)7 min

5.11.3. Practice (Pooled)7 min

5.12.1. Confidence Interval Unpooled t2 min

5.12.2. Example: Confidence Interval (Unpooled)5 min

5.12.3. Practice (Unpooled)

5.13.1. Confidence Interval Pooled t2 min

5.13.2. Example: Confidence Interval w/ Pooled T-test5 min

5.13.3. Practice (Pooled)

5.14.1. One-Way ANOVA8 min

5.14.2. One-Way ANOVA Table10 min

5.14.3. Example9 min

5.14.4. Practice

5.15.1. One-Way ANOVA Hypothesis Test6 min

5.15.2. Example4 min

5.15.3. Practice

5.16.1. Hypothesis Test for a Mean3 min

5.16.2. Example16 min

5.16.3. Example8 min

5.16.4. Practice4 min

5.17.1. Confidence Interval for a Mean13 min

5.17.2. Example4 min

5.17.3. Practice3 min

5.18.1. Central Limit Theorem 5 min

5.18.2. Sampling Distribution for a Mean2 min

5.18.3. Example9 min

5.18.4. Sampling Distribution for a Mean Question5 min

5.19.1. Sampling Distribution of Proportions5 min

5.19.2. Example3 min

5.19.3. Practice4 min

6. Inferential Modeling

1.7hr

6.1.1. Confidence Interval for Linear Regression5 min

6.1.2. Example9 min

6.1.3. Practice3 min

6.1.4. Slope: The Significance of "Zero" (or Lack Thereof)6 min

6.1.5. Practice

6.2.1. Hypothesis Testing for Linear Regression14 min

6.2.2. Example17 min

6.2.3. Example13 min

6.2.4. Practice: Linear Regression Analysis6 min

6.3.1. Prediction Interval of Y7 min

6.3.2. Example12 min

6.3.3. Practice10 min

6.3.4. Practice

7. Basics of Probability

3hr

7.1.1. Events & Sample Spaces6 min

7.1.2. Types of Probability6 min

7.1.3. Probability Language & Notation4 min

7.1.4. Example3 min

7.1.5. Independent vs. Mutually Exclusive Events4 min

7.1.6. Example2 min

7.1.7. Practice

7.2.1. Venn Diagrams3 min

7.2.2. Tree Diagrams4 min

7.2.3. Two-way Table5 min

7.3.1. Interpretation of Probability2 min

7.3.2. Complement Rule3 min

7.3.3. Practice1 min

7.3.4. The Addition Rule4 min

7.4.1. Probability of Independent Events4 min

7.4.2. Example3 min

7.4.3. Practice2 min

7.5.1. Probability of Dependent Events (Conditional Probability)7 min

7.5.2. Conditional Probability: Tree Diagram5 min

7.5.3. Bayes’ Theorem4 min

7.5.4. Example4 min

7.5.5. Practice3 min

7.6.1. Example6 min

7.6.2. Example7 min

7.6.3. Example7 min

7.6.4. Practice4 min

7.6.5. Practice5 min

7.7.1. Summary of Key Definitions6 min

7.8.1. Fundamental Counting Principle6 min

7.8.2. Permutations and Combinations6 min

7.8.3. Practice1 min

7.8.4. Practice54 sec

7.8.5. More Combination Rules3 min

7.8.6. Example4 min

7.8.7. Practice3 min

7.8.8. Practice

7.9.1. Counting and Probability3 min

7.9.3. Practice1 min

7.10.1. Discrete Random Variables8 min

7.10.2. Practice

7.10.3. Probability Distribution Function4 min

7.10.4. Expected Value, Variance, and Standard Deviation of Discrete Random Variables6 min

7.10.5. Example5 min

7.10.6. Example4 min

7.10.7. Practice6 min

7.10.8. Practice4 min

7.10.9. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.1 Mock Exam

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