STAT 2040

University of Guelph

Course Overview

Lessons & Practice

I. Welcome

1. Introduction to Statistics

4min

1.1.1. Introduction to Statistics4 min

2. Gathering Data

1hr

3. Descriptive Statistics

1.3hr

3.1.1. Bar Chart3 min

3.1.2. Practice

3.2.1. Pie Chart3 min

3.2.2. Practice

3.3.1. Histograms4 min

3.3.2. Practice2 min

3.3.3. Practice2 min

3.3.4. Practice

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

3.4.2. Practice3 min

3.5.1. Measures of Central Tendency7 min

3.5.2. Mean and Median Example2 min

3.5.3. Practice

3.5.4. Practice2 min

3.5.5. Practice3 min

3.6.1. Skewness and Symmetry 6 min

3.6.2. Practice

3.7.1. Range and Interquartile Range11 min

3.7.2. Variance and Standard Deviation6 min

3.7.3. Practice3 min

3.7.4. Practice3 min

3.7.5. Practice

3.8.1. Percentiles4 min

3.8.2. Example2 min

3.8.3. Practice

3.9.1. Boxplots and Five Number Summary9 min

3.9.2. Practice4 min

3.9.3. Practice

3.10.1. Transforming Data

3.10.2. Practice

4. Probability

1.9hr

4.1.1. Events & Sample Spaces6 min

4.1.2. Types of Probability6 min

4.1.3. Probability Language & Notation4 min

4.1.4. Example3 min

4.1.5. Independent vs. Mutually Exclusive Events4 min

4.1.6. Example2 min

4.1.7. Practice

4.2.1. Venn Diagrams3 min

4.2.2. Tree Diagrams4 min

4.2.3. Two-way Table5 min

4.3.1. Interpretation of Probability2 min

4.3.2. Complement Rule3 min

4.3.3. Practice1 min

4.3.4. The Addition Rule4 min

4.4.1. Probability of Independent Events4 min

4.4.2. Example3 min

4.4.3. Practice2 min

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

4.5.2. Conditional Probability: Tree Diagram5 min

4.5.3. Bayes’ Theorem4 min

4.5.4. Example4 min

4.5.5. Practice3 min

4.6.1. Example6 min

4.6.2. Example7 min

4.6.3. Example7 min

4.6.4. Practice4 min

4.6.5. Practice5 min

4.7.1. Summary of Key Definitions6 min

5. Discrete Random Variables & Discrete Probability Distribution

1.9hr

5.1.1. Discrete Random Variables8 min

5.1.2. Probability Distribution Function4 min

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

5.1.4. Example5 min

5.1.5. Example4 min

5.1.6. Practice

5.1.7. Practice6 min

5.1.8. Pratice4 min

5.1.9. Practice

5.2.1. Binomial Experiment4 min

5.2.2. Binomial Distribution8 min

5.2.3. Example10 min

5.2.4. Example1 min

5.2.5. Practice6 min

5.2.6. Practice

5.3.1. Poisson Experiment5 min

5.3.2. Poisson Distribution1 min

5.3.3. Example3 min

5.3.4. Practice5 min

5.3.5. Practice5 min

5.4.1. Approximating the Binomial Distribution with Poisson2 min

5.4.2. Example6 min

5.4.3. Practice

5.5.1. Hypergeometric Experiment5 min

5.5.2. Hypergeometric Distribution9 min

5.5.3. Example4 min

5.5.4. Practice4 min

5.5.5. Practice Question

6. Continuous Random Variables and Continuous Probability Distributions

1.3hr

6.1.1. Continuous Probability Distribution Theory10 min

6.2.1. Uniform Distribution1 min

6.2.2. Practice3 min

6.3.1. Normal Distribution11 min

6.3.2. Practice5 min

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

6.4.2. Standardizing a Normal Random Variable4 min

6.4.3. Example10 min

6.4.4. Practice6 min

6.4.5. Practice3 min

6.5.1. Normal Approximation to Binomial2 min

6.5.2. Practice5 min

6.5.3. Normal Approximation to the Binomial Distribution Question4 min

6.5.4. Normal Approximation to the Binomial Distribution Question4 min

7. Sampling Distributions

59min

7.1.1. Sampling Variability & Sampling Distribution12 min

7.2.1. Central Limit Theorem 5 min

7.2.2. Sampling Distribution for a Mean2 min

7.2.3. Example9 min

7.2.4. Sampling Distribution for a Mean Question5 min

7.3.1. Sampling Distribution of Proportions5 min

7.3.2. Example3 min

7.3.3. Sampling Distribution of Proportions4 min

7.4.1. Drawing Samples From a Finite Population8 min

7.4.2. Example4 min

7.4.3. Practice3 min

8. Confidence Intervals

37min

8.1.1. Introduction to Confidence Intervals14 min

8.2.1. Confidence Interval for a Mean13 min

8.2.2. Example4 min

8.2.3. Practice3 min

8.3.1. Margin of Error and Sample Size3 min

8.3.2. Practice

9. Hypothesis Testing

1.4hr

9.1.1. Introduction to Hypothesis Testing 15 min

9.1.2. Hypothesis Testing Steps25 min

9.2.1. Hypothesis Test for a Mean3 min

9.2.2. Example16 min

9.2.3. Example8 min

9.2.4. Practice4 min

9.3.1. Type I and Type II Errors5 min

9.3.2. Type I and Type II Errors1 min

9.3.3. Practice

9.3.4. Practice

9.3.5. Power7 min

9.3.6. Practice

10. Inference for Two Means

2.2hr

10.1.1. Comparing Two Independent Means9 min

10.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

10.2.2. Example (Unpooled)11 min

10.2.3. Practice (Unpooled)5 min

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

10.3.2. Example (Pooled)7 min

10.3.3. Practice (Pooled)7 min

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

10.4.2. Confidence Interval for Two Means Containing Zero7 min

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

10.5.1. Confidence Interval Unpooled t2 min

10.5.2. Example: Confidence Interval (Unpooled)5 min

10.5.3. Practice (Unpooled)

10.6.1. Confidence Interval Formula Pooled t2 min

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

10.6.3. Practice (Pooled)

10.7.1. Match Pairs for Dependent Means12 min

10.8.1. Hypothesis Test for Matched Pairs11 min

10.8.2. Example7 min

10.8.3. Practice3 min

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

10.9.2. Practice

11. Inference for Proportions

1.5hr

11.1.1. Confidence Interval for a Proportion2 min

11.1.2. Example5 min

11.1.3. Practice4 min

11.2.1. Hypothesis Test for a Proportion10 min

11.2.2. Example4 min

11.2.3. Practice5 min

11.2.4. Practice9 min

11.3.1. Confidence Interval for Differences in Population Proportions3 min

11.3.2. Confidence Interval for Two Proportions1 min

11.3.3. Example4 min

11.3.4. Practice4 min

11.4.1. Hypothesis Testing for Two Independent Population Proportions9 min

11.4.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

11.4.3. Example13 min

11.4.4. Practice (Pooled)6 min

12. Inference for Variances

1.3hr

12.1.1. Inference for Population Variance & Chi-square Distribution 8 min

12.2.1. Confidence Interval for Population Variance5 min

12.2.2. Example6 min

12.2.3. Pratice3 min

12.2.4. Practice

12.3.1. Hypothesis Test for Population Variance8 min

12.3.2. Example8 min

12.3.3. Hypothesis Test for Population Variance

12.3.4. Practice4 min

12.4.1. Test of Equality of Two Variances7 min

12.5.1. F-Test for Equality of Two Variances11 min

12.5.2. Example6 min

12.5.3. F-Test for Equality of Two Variances

12.6.1. Levene’s Test for the Equality of Two Variances4 min

12.6.2. Example7 min

12.6.3. Practice

13. Chi-Square Tests for Count Data

48min

13.1.1. Types of Chi Square Tests8 min

13.1.2. Chi-Square Test for "Goodness of Fit"4 min

13.1.3. Example7 min

13.1.4. Pratice9 min

13.1.5. Chi-Square Test for Independence5 min

13.1.6. Example8 min

13.1.7. Practice4 min

13.1.8. More on Chi-Square Tests3 min

14. One-Way Analysis of Variance (ANOVA)

38min

14.1.1. One-Way ANOVA8 min

14.1.2. One-Way ANOVA Table10 min

14.1.3. Example9 min

14.2.1. One-Way ANOVA Hypothesis Test6 min

14.2.2. One-way ANOVA4 min

14.2.3. Practice

14.2.4. One-way ANOVA16 Qns

15. Introduction to Simple Linear Regression

1.4hr

15.1.1. Scatterplots5 min

15.1.2. Practice

15.2.1. Correlation5 min

15.2.2. Practice

15.3.1. Solving for Correlation2 min

15.3.2. Example6 min

15.3.3. Practice4 min

15.3.4. Example3 min

15.3.5. Practice

15.4.1. Coefficient of Determination (R Squared)7 min

15.4.2. Assessing Goodness of Fit6 min

15.4.3. Practice

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

15.5.2. Example7 min

15.5.3. Practice (Version 1)3 min

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

15.5.5. Example5 min

15.5.6. Practice (Version 2)5 min

15.6.1. Predictions3 min

15.6.2. Residuals (Errors)5 min

15.6.3. Practice

15.6.4. Residual Plots2 min

15.6.5. Regression Diagnostics 5 min

15.6.6. Practice

15.6.7. Standard Deviation of the Residuals5 min

15.6.8. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.4. Term Test #1 - Mock Assessment31 Qns

ME.5. Term Test #2 - Mock Assessment20 Qns

ME.6. Final Exam - Mock Assessment35 Qns

ME.6 Final Exam - Mock Assessment

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Final Exam - Mock Assessment

This mock exam has 35 questions

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