STA220H1

U of T

Course Overview

Lessons & Practice

I. Welcome

1. Summarizing Data: One Variable

1.8hr

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. Dot Plots5 min

1.2.2. Practice

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

1.3.2. Practice3 min

1.4.1. Histograms4 min

1.4.2. Practice2 min

1.4.3. Practice2 min

1.4.4. Practice

1.5.1. Bar Chart3 min

1.5.2. Practice

1.6.1. Pie Chart3 min

1.6.2. Practice

1.7.1. Boxplots and Five Number Summary9 min

1.7.2. Practice4 min

1.7.3. Practice

1.8.1. Measures of Central Tendency7 min

1.8.2. Mean and Median Example2 min

1.8.3. Practice

1.8.4. Practice2 min

1.8.5. Practice3 min

1.9.1. Range and Interquartile Range11 min

1.9.2. Variance and Standard Deviation6 min

1.9.3. Practice3 min

1.9.4. Practice3 min

1.9.5. Practice

1.10.1. Histograms4 min

1.10.2. Practice2 min

1.10.3. Practice2 min

1.10.4. Practice

1.10.5. Skewness and Symmetry 6 min

1.10.6. Practice

2. Summarizing Data: Relationships Between Variables

38min

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

2.1.2. Practice4 min

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

2.2.2. Simpson’s Paradox3 min

2.2.3. Practice

2.3.1. Winter 2019 Midterm Exam # 18

2.4.1. Scatterplots5 min

2.4.2. Practice

2.5.1. Correlation5 min

2.5.2. Practice

2.6.1. Solving for Correlation2 min

2.6.2. Example6 min

2.6.3. Practice

2.6.4. Example3 min

2.6.5. Practice4 min

3. Probability: Events

1.9hr

3.1.1. Events & Sample Spaces6 min

3.1.2. Types of Probability6 min

3.1.3. Probability Language & Notation4 min

3.1.4. Example3 min

3.1.5. Independent vs. Mutually Exclusive Events4 min

3.1.6. Example2 min

3.1.7. Practice

3.2.1. Venn Diagrams3 min

3.2.2. Tree Diagrams4 min

3.2.3. Two-way Table5 min

3.3.1. Interpretation of Probability2 min

3.3.2. Complement Rule3 min

3.3.3. Practice1 min

3.3.4. The Addition Rule4 min

3.4.1. Probability of Independent Events4 min

3.4.2. Example3 min

3.4.3. Practice2 min

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

3.5.2. Conditional Probability: Tree Diagram5 min

3.5.3. Bayes’ Theorem4 min

3.5.4. Example4 min

3.5.5. Practice3 min

3.6.1. Example6 min

3.6.2. Example7 min

3.6.3. Example7 min

3.6.4. Practice4 min

3.6.5. Practice5 min

3.7.1. Summary of Key Definitions6 min

4. Probability: Random Variables

2.2hr

4.1.1. Discrete Random Variables8 min

4.1.2. Probability Distribution Function4 min

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

4.1.4. Example5 min

4.1.5. Example4 min

4.1.6. Practice

4.1.7. Practice6 min

4.1.8. Pratice4 min

4.1.9. Practice

4.2.1. Binomial Experiment4 min

4.2.2. Binomial Distribution8 min

4.2.3. Example10 min

4.2.4. Example1 min

4.2.5. Practice6 min

4.2.6. Practice

4.3.1. Continuous Probability Distribution Theory10 min

4.4.1. Uniform Distribution1 min

4.4.2. Practice3 min

4.5.1. Normal Distribution11 min

4.5.2. Practice5 min

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

4.6.2. Standardizing a Normal Random Variable4 min

4.6.3. Example10 min

4.6.4. Practice6 min

4.6.5. Practice3 min

5. Sampling Distribution

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. Sampling Distribution of Proportions4 min

5.4.1. Drawing Samples From a Finite Population8 min

5.4.2. Example4 min

5.4.3. Practice3 min

7. Confidence Intervals Part 1

17min

7.1.1. Introduction to Confidence Intervals14 min

7.2.1. Margin of Error and Sample Size3 min

7.2.2. Practice

8. Confidence Intervals Part 2

31min

8.1.1. Confidence Interval for a Mean13 min

8.1.2. Example4 min

8.1.3. Practice3 min

8.2.1. Confidence Interval for a Proportion2 min

8.2.2. Example5 min

8.2.3. Practice4 min

9. The Process of Statistical Tests

1.7hr

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. Hypothesis Test for a Proportion10 min

9.3.2. Example4 min

9.3.3. Practice5 min

9.3.4. Practice9 min

10. The Effective Use of Statistical Tests

14min

10.1.1. Type I and Type II Errors5 min

10.1.2. Type I and Type II Errors1 min

10.1.3. Practice

10.1.4. Practice

10.1.5. Power7 min

10.1.6. Practice

11. Comparing Two Groups

2.5hr

11.1.1. Comparing Two Independent Means9 min

11.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

11.1.4. Example (Pooled)7 min

11.1.5. Practice (Pooled)7 min

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

11.2.2. Confidence Interval for Two Means Containing Zero7 min

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

11.2.4. Confidence Interval Formula Pooled t2 min

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

11.2.6. Practice (Pooled)

11.3.1. Match Pairs for Dependent Means12 min

11.4.1. Hypothesis Test for Matched Pairs11 min

11.4.2. Example7 min

11.4.3. Practice3 min

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

11.5.2. Practice

11.6.1. Hypothesis Testing for Two Independent Population Proportions9 min

11.6.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

11.6.3. Example13 min

11.6.4. Practice (Pooled)6 min

11.7.1. Confidence Interval for Differences in Population Proportions3 min

11.7.2. Confidence Interval for Two Proportions1 min

11.7.3. Example4 min

11.7.4. Practice4 min

12. Simple Linear Regression

2.6hr

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

12.1.2. Example7 min

12.1.3. Practice (Version 1)3 min

12.2.1. Predictions3 min

12.2.2. Residuals (Errors)5 min

12.2.3. Practice

12.2.4. Residual Plots2 min

12.2.5. Regression Diagnostics 5 min

12.2.6. Practice

12.2.7. Standard Deviation of the Residuals5 min

12.2.8. Practice

12.3.1. Coefficient of Determination (R Squared)7 min

12.3.2. Assessing Goodness of Fit6 min

12.3.3. Practice

12.4.1. Estimating the Coefficients of the Linear Regression Model9 min

12.4.2. Measures of Variation in Regression9 min

12.4.3. Practice

12.5.1. Standard Error and R Square Formulas7 min

12.5.2. Example5 min

12.5.3. Practice4 min

12.6.1. Hypothesis Testing for Linear Regression14 min

12.6.2. Example17 min

12.6.3. Example13 min

12.6.4. Practice: Linear Regression Analysis6 min

12.7.1. Prediction Interval of Y7 min

12.7.2. Example12 min

12.7.3. Practice10 min

12.7.4. Practice

Mock Exams

ME.1. Term Test - Mock Assessment31 Qns

ME.2. Final Assessment - Mock Assessment35 Qns

ME.2 Final Assessment - Mock Assessment

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Final Assessment - Mock Assessment

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