STAT 1060

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Course Overview

Lessons & Practice

I. Welcome

1. Intro to Stats

11min

1.1.1. Introduction to Statistics4 min

1.1.2. Measurement Scales7 min

1.1.3. Practice

2. Displaying & Summarizing Categorical Data

20min

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

3. Displaying & Summarizing Quantitative Data

1.3hr

3.1.1. Histograms4 min

3.1.2. Practice2 min

3.1.3. Practice2 min

3.1.4. Practice

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

3.2.2. Practice3 min

3.3.1. Measures of Central Tendency7 min

3.3.2. Mean and Median Example2 min

3.3.3. Practice

3.3.4. Practice2 min

3.3.5. Practice3 min

3.4.1. Skewness and Symmetry 6 min

3.4.2. Practice

3.5.1. Percentiles4 min

3.5.2. Example2 min

3.5.3. Practice

3.6.1. Range and Interquartile Range11 min

3.6.2. Variance and Standard Deviation6 min

3.6.3. Practice3 min

3.6.4. Practice3 min

3.6.5. Practice

3.7.1. Boxplots and Five Number Summary9 min

3.7.2. Practice4 min

3.7.3. Practice

3.8.1. Summary & Comparing Distributions

3.8.2. Practice

3.8.3. Practice

3.8.4. Practice

3.8.5. Practice

4. Exploratory Data Analysis

49min

4.1.1. Measures of Central Tendency7 min

4.1.2. Mean and Median Example2 min

4.1.3. Practice

4.1.4. Practice2 min

4.1.5. Practice3 min

4.2.1. Skewness and Symmetry 6 min

4.2.2. Practice

4.3.1. Percentiles4 min

4.3.2. Example2 min

4.3.3. Practice

4.4.1. Range and Interquartile Range11 min

4.4.2. Variance and Standard Deviation6 min

4.4.3. Practice3 min

4.4.4. Practice3 min

4.4.5. Practice

5. Scatterplots, Association, and Correlation

37min

5.1.1. Scatterplots5 min

5.1.2. Practice

5.2.1. Correlation5 min

5.2.2. Practice

5.3.1. Solving for Correlation2 min

5.3.2. Example6 min

5.3.3. Practice

5.3.4. Practice4 min

5.3.5. Example3 min

5.4.1. Coefficient of Determination (R Squared)7 min

5.4.2. Assessing Goodness of Fit6 min

5.4.3. Practice

6. Simple Linear Regression

45min

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

6.1.2. Example7 min

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

6.1.4. Practice (Version 1)3 min

6.1.5. Practice (Version 2)5 min

6.1.6. Example5 min

6.2.1. Predictions3 min

6.2.2. Residuals (Errors)5 min

6.2.3. Practice

6.2.4. Residual Plots2 min

6.2.5. Regression Diagnostics 5 min

6.2.6. Practice

6.2.7. Standard Deviation of the Residuals5 min

6.2.8. Practice

7. Sample Survey

33min

7.1.1. Sample vs. Population7 min

7.1.2. Practice

7.2.1. Statistical Sampling28 sec

7.2.2. Convenience Sampling1 min

7.2.3. Simple Random Sampling3 min

7.2.4. Systematic Sampling2 min

7.2.5. Stratified Sampling vs. Cluster Sampling6 min

7.2.6. Two-Stage Cluster Sampling2 min

7.2.7. Practice

7.2.8. Practice

7.2.9. Practice

7.3.1. Sampling Bias7 min

7.3.2. Recipe for a Good Sample5 min

7.3.3. Practice

7.3.4. Practice

8. Experiments and Observational Studies

23min

8.1.1. Observational Studies4 min

8.1.2. Experimental Studies3 min

8.1.3. Example5 min

8.1.4. Practice

8.2.1. Types of Experimental Designs7 min

8.2.2. Principles of Experimental Design4 min

8.2.4. Practice

8.2.5. Practice

9. Probability

1.9hr

9.1.1. Events & Sample Spaces6 min

9.1.2. Types of Probability6 min

9.1.3. Probability Language & Notation4 min

9.1.4. Example3 min

9.1.5. Independent vs. Mutually Exclusive Events4 min

9.1.6. Example2 min

9.1.7. Practice

9.2.1. Venn Diagrams3 min

9.2.2. Tree Diagrams4 min

9.2.3. Two-way Table5 min

9.3.1. Interpretation of Probability2 min

9.3.2. Complement Rule3 min

9.3.3. Practice1 min

9.3.4. The Addition Rule4 min

9.4.1. Probability of Independent Events4 min

9.4.2. Example3 min

9.4.3. Practice2 min

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

9.5.2. Conditional Probability: Tree Diagram5 min

9.5.3. Bayes’ Theorem4 min

9.5.4. Example4 min

9.5.5. Practice3 min

9.6.1. Example6 min

9.6.2. Example7 min

9.6.3. Example7 min

9.6.4. Practice4 min

9.6.5. Practice5 min

9.7.1. Summary of Key Definitions6 min

10. Random Variables

36min

10.1.1. Discrete Random Variables8 min

10.1.2. Probability Distribution Function4 min

10.1.3. Example4 min

10.1.4. Practice

10.1.5. Practice6 min

10.1.6. Pratice4 min

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

10.2.2. Example5 min

10.2.3. Practice

10.3.1. Linear Combinations of Random Variables

10.3.2. Example

10.3.3. Example

10.3.4. Practice

11. Discrete Probability Distributions

37min

11.1.1. Bernoulli Trials4 min

11.1.2. Practice4 min

11.1.3. Binomial Experiment4 min

11.1.4. Binomial Distribution8 min

11.1.5. Example10 min

11.1.6. Example1 min

11.1.7. Practice6 min

11.1.8. Practice

12. Continuous Probability Distributions & the Normal Model

1.2hr

12.1.1. Continuous Probability Distribution Theory10 min

12.2.1. Normal Distribution11 min

12.2.2. Practice5 min

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

12.3.2. Standardizing a Normal Random Variable4 min

12.3.3. Example10 min

12.3.4. Practice6 min

12.3.5. Practice3 min

12.4.1. Normal Approximation to Binomial2 min

12.4.2. Practice5 min

12.4.3. Normal Approximation to the Binomial Distribution Question4 min

12.4.4. Normal Approximation to the Binomial Distribution Question4 min

13. Sampling Distribution

59min

13.1.1. Sampling Variability & Sampling Distribution12 min

13.2.1. Central Limit Theorem 5 min

13.2.2. Sampling Distribution for a Mean2 min

13.2.3. Example9 min

13.2.4. Sampling Distribution for a Mean Question5 min

13.3.1. Sampling Distribution of Proportions5 min

13.3.2. Example3 min

13.3.3. Sampling Distribution of Proportions4 min

13.4.1. Drawing Samples From a Finite Population8 min

13.4.2. Example4 min

13.4.3. Practice3 min

14. Confidence Interval for Proportions

27min

14.1.1. Introduction to Confidence Intervals14 min

14.2.1. Confidence Interval for a Proportion2 min

14.2.2. Example5 min

14.2.3. Practice4 min

14.3.1. Margin of Error and Sample Size3 min

14.3.2. Practice

15. Hypothesis Testing for Proportions

1.4hr

15.1.1. Introduction to Hypothesis Testing 15 min

15.1.2. Hypothesis Testing Steps25 min

15.2.1. Hypothesis Test for a Proportion10 min

15.2.2. Example4 min

15.2.3. Practice5 min

15.2.4. Practice9 min

15.3.1. Type I and Type II Errors5 min

15.3.2. Type I and Type II Errors1 min

15.3.3. Practice

15.3.4. Practice

15.3.5. Power7 min

15.3.6. Practice

16. Inferences About Means

52min

16.1.1. Confidence Interval for a Mean13 min

16.1.2. Example4 min

16.1.3. Practice3 min

16.2.1. Hypothesis Test for a Mean3 min

16.2.2. Example16 min

16.2.3. Example8 min

16.2.4. Practice4 min

17. Comparing Means

1.6hr

17.1.1. Comparing Two Independent Means9 min

17.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

17.2.2. Example (Unpooled)11 min

17.2.3. Practice (Unpooled)5 min

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

17.3.2. Example (Pooled)7 min

17.3.3. Practice (Pooled)7 min

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

17.4.2. Confidence Interval for Two Means Containing Zero7 min

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

17.5.1. Confidence Interval Unpooled t2 min

17.5.2. Example: Confidence Interval (Unpooled)5 min

17.5.3. Practice (Unpooled)

17.6.1. Confidence Interval Formula Pooled t2 min

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

17.6.3. Practice (Pooled)

18. Paired Samples (Matched Pairs)

37min

18.1.1. Match Pairs for Dependent Means12 min

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

18.2.2. Practice

18.3.1. Hypothesis Test for Matched Pairs11 min

18.3.2. Example7 min

18.3.3. Practice3 min

19. Inference for Two Population Proportions

49min

19.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

19.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

19.1.3. Example13 min

19.1.4. Practice (Pooled)6 min

19.2.1. Confidence Interval for Differences in Population Proportions3 min

19.2.2. Confidence Interval for Two Proportions1 min

19.2.3. Example4 min

19.2.4. Practice4 min

20. Chi-Square

48min

20.1.1. Types of Chi Square Tests8 min

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

20.1.3. Example7 min

20.1.4. Pratice9 min

20.1.5. Chi-Square Test for Independence5 min

20.1.6. Example8 min

20.1.7. Practice4 min

20.1.8. More on Chi-Square Tests3 min

21. Inference for Linear Regression

2.2hr

21.1.1. Estimating the Coefficients of the Linear Regression Model9 min

21.1.2. Measures of Variation in Regression9 min

21.1.3. Practice

21.2.1. Standard Error and R Square Formulas7 min

21.2.2. Example5 min

21.2.3. Practice4 min

21.3.1. Confidence Interval for Linear Regression5 min

21.3.2. Example9 min

21.3.3. Practice3 min

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

21.3.5. Practice

21.4.1. Hypothesis Testing for Linear Regression14 min

21.4.2. Example17 min

21.4.3. Example13 min

21.4.4. Practice: Linear Regression Analysis6 min

21.5.1. Prediction Interval of Y7 min

21.5.2. Example12 min

21.5.3. Practice10 min

21.5.4. Practice

22. Analysis of Variance

38min

22.1.1. One-Way ANOVA8 min

22.1.2. One-Way ANOVA Table10 min

22.1.3. Example9 min

22.1.4. Practice

22.2.1. One-Way ANOVA Hypothesis Test6 min

22.2.2. Example4 min

22.2.3. Practice

Mock Exams

ME.1. Exam 1 (Midterm Exam) - Mock Assessment20 Qns

ME.2. Final Exam - Mock Assessment39 Qns

ME.1 Exam 1 (Midterm Exam) - Mock Assessment

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Exam 1 (Midterm Exam) - Mock Assessment

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