STATS 2244A/B

UWO

Course Overview

Grade Boosters

Lessons & Practice

I. Welcome

1. Intro to Stats and Sampling

44min

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

2. Experiments and Observational Studies

23min

2.1.1. Observational Studies4 min

2.1.2. Experimental Studies3 min

2.1.3. Example5 min

2.1.4. Practice

2.2.1. Types of Experimental Designs7 min

2.2.2. Principles of Experimental Design4 min

2.2.4. Practice

2.2.5. Practice

3. Exploring and Summarizing Data

49min

3.1.1. Measures of Central Tendency7 min

3.1.2. Mean and Median Example2 min

3.1.3. Practice

3.1.4. Practice2 min

3.1.5. Practice3 min

3.2.1. Skewness and Symmetry 6 min

3.2.2. Practice

3.3.1. Percentiles4 min

3.3.2. Example2 min

3.3.3. Practice

3.4.1. Range and Interquartile Range11 min

3.4.2. Variance and Standard Deviation6 min

3.4.3. Practice3 min

3.4.4. Practice3 min

3.4.5. Practice

4. Displaying & Summarizing Quantitative Data

1.4hr

4.1.1. Histograms4 min

4.1.2. Practice2 min

4.1.3. Practice2 min

4.1.4. Practice

4.2.1. Frequency Polygons2 min

4.2.2. Practice4 min

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

4.3.2. Practice3 min

4.4.1. Measures of Central Tendency7 min

4.4.2. Mean and Median Example2 min

4.4.3. Practice

4.4.4. Practice2 min

4.4.5. Practice3 min

4.5.1. Skewness and Symmetry 6 min

4.5.2. Practice

4.6.1. Percentiles4 min

4.6.2. Example2 min

4.6.3. Practice

4.7.1. Range and Interquartile Range11 min

4.7.2. Variance and Standard Deviation6 min

4.7.3. Practice3 min

4.7.4. Practice3 min

4.7.5. Practice

4.8.1. Boxplots and Five Number Summary9 min

4.8.2. Practice4 min

4.8.3. Practice

5. Discrete Random Variables

1.2hr

5.1.1. Discrete Random Variables8 min

5.1.2. Probability Distribution Function4 min

5.1.3. Example4 min

5.1.4. Practice

5.1.5. Practice6 min

5.1.6. Pratice4 min

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

5.2.2. Example5 min

5.2.3. Practice

5.3.1. Bernoulli Trials4 min

5.3.2. Practice4 min

5.3.3. Binomial Experiment4 min

5.3.4. Binomial Distribution8 min

5.3.5. Example10 min

5.3.6. Example1 min

5.3.7. Practice6 min

5.3.8. Practice

6. Continuous Probability Distributions

1.1hr

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

7. Sampling Distribution

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. Estimating with Confidence Intervals

48min

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. Confidence Interval for a Proportion2 min

8.3.2. Example5 min

8.3.3. Practice4 min

8.4.1. Margin of Error and Sample Size3 min

8.4.2. Practice

9. Hypothesis Testing with One Sample

1.9hr

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

9.4.1. Type I and Type II Errors5 min

9.4.2. Type I and Type II Errors1 min

9.4.3. Practice

9.4.4. Practice

9.4.5. Power7 min

9.4.6. Practice

10. Inference for Two Population Means

1.6hr

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)

11. Inference for Two Population Proportions

49min

11.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

11.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

11.1.3. Example13 min

11.1.4. Practice (Pooled)6 min

11.2.1. Confidence Interval for Differences in Population Proportions3 min

11.2.2. Confidence Interval for Two Proportions1 min

11.2.3. Example4 min

11.2.4. Practice4 min

12. Scatterplots, Association, and Correlation

37min

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. Practice

12.3.4. Practice4 min

12.3.5. Example3 min

12.4.1. Coefficient of Determination (R Squared)7 min

12.4.2. Assessing Goodness of Fit6 min

12.4.3. Practice

13. Simple Linear Regression

2.8hr

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

13.1.2. Example7 min

13.1.3. Practice (Version 1)3 min

13.2.1. Predictions3 min

13.2.2. Residuals (Errors)5 min

13.2.3. Practice

13.2.4. Residual Plots2 min

13.2.5. Regression Diagnostics 5 min

13.2.6. Practice

13.2.7. Standard Deviation of the Residuals5 min

13.2.8. Practice

13.3.1. Estimating the Coefficients of the Linear Regression Model9 min

13.3.2. Measures of Variation in Regression9 min

13.3.3. Practice

13.4.1. Standard Error and R Square Formulas7 min

13.4.2. Example5 min

13.4.3. Practice4 min

13.5.1. Confidence Interval for Linear Regression5 min

13.5.2. Example9 min

13.5.3. Practice3 min

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

13.5.5. Practice

13.6.1. Hypothesis Testing for Linear Regression14 min

13.6.2. Example17 min

13.6.3. Example13 min

13.6.4. Practice: Linear Regression Analysis6 min

13.7.1. Prediction Interval of Y7 min

13.7.2. Example12 min

13.7.3. Practice10 min

13.7.4. Practice

14. One-factor 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

15. Post-Hoc Tests

15.1.1. Tukey’s Honest Significance Difference Multiple Comparison Method

15.1.2. Tukey’s Honest Significance Difference Multiple Comparison Method

15.2.1. Kruskal-Wallis Procedure

15.2.2. Kruskal-Wallis Procedure

15.2.3. Kruskal-Wallis Procedure

Mock Exams

ME.1. Midterm - Mock Assessment25 Qns

ME.2. Final Exam - Mock Assessment37 Qns

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