MATH 2930

York U

Course Overview

Lessons & Practice

I. Welcome

1. Overview and Descriptive Statistics

1.5hr

1.1.1. Introduction to Statistics4 min

1.1.2. Sample vs. Population7 min

1.1.3. Practice

1.1.4. Measurement Scales7 min

1.1.5. Practice

1.2.1. Statistical Sampling28 sec

1.2.2. Convenience Sampling1 min

1.2.3. Simple Random Sampling3 min

1.2.4. Systematic Sampling2 min

1.2.5. Stratified Sampling vs. Cluster Sampling6 min

1.2.6. Two-Stage Cluster Sampling2 min

1.2.7. Practice

1.2.8. Practice

1.2.9. Practice

1.3.1. Sampling Bias7 min

1.3.2. Recipe for a Good Sample5 min

1.3.3. Practice

1.3.4. Practice

1.4.1. Measures of Central Tendency7 min

1.4.2. Mean and Median Example2 min

1.4.3. Practice

1.4.4. Practice2 min

1.4.5. Practice3 min

1.5.1. Skewness and Symmetry 6 min

1.5.2. Practice

1.6.1. Percentiles4 min

1.6.2. Example2 min

1.6.3. Practice

1.7.1. Range and Interquartile Range11 min

1.7.2. Variance and Standard Deviation6 min

1.7.3. Practice3 min

1.7.4. Practice3 min

1.7.5. Practice

2. Probability

1.9hr

2.1.1. Events & Sample Spaces6 min

2.1.2. Types of Probability6 min

2.1.3. Probability Language & Notation4 min

2.1.4. Example3 min

2.1.5. Independent vs. Mutually Exclusive Events4 min

2.1.6. Example2 min

2.1.7. Practice

2.2.1. Venn Diagrams3 min

2.2.2. Tree Diagrams4 min

2.2.3. Two-way Table5 min

2.3.1. Interpretation of Probability2 min

2.3.2. Complement Rule3 min

2.3.3. Practice1 min

2.3.4. The Addition Rule4 min

2.4.1. Probability of Independent Events4 min

2.4.2. Example3 min

2.4.3. Practice2 min

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

2.5.2. Conditional Probability: Tree Diagram5 min

2.5.3. Bayes’ Theorem4 min

2.5.4. Example4 min

2.5.5. Practice3 min

2.6.1. Example6 min

2.6.2. Example7 min

2.6.3. Example7 min

2.6.4. Practice4 min

2.6.5. Practice5 min

2.7.1. Summary of Key Definitions6 min

4. Continuous Random Variables and Probability Distributions

1.2hr

4.1.1. Continuous Probability Distribution Theory10 min

4.2.1. Normal Distribution11 min

4.2.2. Practice5 min

4.3.1. Standard Normal Distribution (Z-Scores)11 min

4.3.2. Standardizing a Normal Random Variable4 min

4.3.3. Example10 min

4.3.4. Practice6 min

4.3.5. Practice3 min

4.4.1. Normal Approximation to Binomial2 min

4.4.2. Practice5 min

4.4.3. Practice4 min

4.4.4. Practice4 min

5. Joint Probability Distributions and Random Samples

59min

5.1.1. Sampling Variability & Sampling Distribution12 min

5.2.1. Central Limit Theorem 5 min

5.2.2. Sampling Distribution for a Mean2 min

5.2.3. Example9 min

5.2.4. Sampling Distribution for a Mean Question5 min

5.3.1. Sampling Distribution of Proportions5 min

5.3.2. Example3 min

5.3.3. Practice4 min

5.4.1. Drawing Samples From a Finite Population8 min

5.4.2. Example4 min

5.4.3. Practice3 min

6. Skip

7. Statistical Intervals Based on a Single Sample

37min

7.1.1. Introduction to Confidence Intervals14 min

7.2.1. Confidence Interval for a Mean13 min

7.2.2. Example4 min

7.2.3. Practice3 min

7.3.1. Margin of Error and Sample Size3 min

7.3.2. Practice

8. Tests of Hypothesis Based on a Single Sample

1.4hr

8.1.1. Introduction to Hypothesis Testing 15 min

8.1.2. Hypothesis Testing Steps25 min

8.2.1. Hypothesis Test for a Mean3 min

8.2.2. Example16 min

8.2.3. Example8 min

8.2.4. Practice4 min

8.3.1. Type I and Type II Errors5 min

8.3.2. Type I and Type II Errors1 min

8.3.3. Practice

8.3.4. Practice

8.3.5. Power7 min

8.3.6. Practice

9. Skip

10. The Analysis of Variance

38min

10.1.1. One-Way ANOVA8 min

10.1.2. One-Way ANOVA Table10 min

10.1.3. Example9 min

10.1.4. Practice

10.2.1. One-Way ANOVA Hypothesis Test6 min

10.2.2. Example4 min

10.2.3. Practice

11. Skip

12. Simple Linear Regression and Correlation

1.4hr

12.1.1. Scatterplots5 min

12.1.2. Practice

12.2.1. Correlation5 min

12.2.2. Practice

12.3.1. Solving for Correlation2 min

12.3.2. Example6 min

12.3.3. Practice4 min

12.3.4. Example3 min

12.3.5. Practice

12.4.1. Coefficient of Determination (R Squared)7 min

12.4.2. Assessing Goodness of Fit6 min

12.4.3. Practice

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

12.5.2. Example7 min

12.5.3. Practice (Version 1)3 min

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

12.5.5. Example5 min

12.5.6. Practice (Version 2)5 min

12.6.1. Predictions3 min

12.6.2. Residuals (Errors)5 min

12.6.3. Practice

12.6.4. Residual Plots2 min

12.6.5. Regression Diagnostics 5 min

12.6.6. Practice

12.6.7. Standard Deviation of the Residuals5 min

12.6.8. Practice

13. Nonlinear and Multiple Regression

30min

13.1.1. Assessing a Multiple Regression Model5 min

13.1.2. F-test for Multiple Regression5 min

13.1.3. Solving for the F-score9 min

13.1.4. Example2 min

13.1.5. Practice8 min

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.4. Test 1 - Mock Assessment20 Qns

ME.5. Test 2 - Mock Assessment18 Qns

ME.6. Final Exam - Mock Assessment22 Qns

ME.4 Test 1 - Mock Assessment

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Test 1 - Mock Assessment

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