QMS 210

TMU

Course Overview

Lessons & Practice

I. Welcome

1. Collecting Data & 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. 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

37min

3.1.1. Boxplots and Five Number Summary9 min

3.1.2. Practice4 min

3.1.3. Practice

3.2.1. Histograms4 min

3.2.2. Practice2 min

3.2.3. Practice2 min

3.2.4. Practice

3.3.1. Frequency Polygons2 min

3.3.2. Practice4 min

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

3.4.2. Practice3 min

3.5.1. Times Series Plots2 min

3.5.2. Practice2 min

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. Discrete Random Variables

36min

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

6. Discrete Probability Distributions

1.1hr

6.1.1. Bernoulli Trials4 min

6.1.2. Practice4 min

6.1.3. Binomial Experiment4 min

6.1.4. Binomial Distribution8 min

6.1.5. Example10 min

6.1.6. Example1 min

6.1.7. Practice6 min

6.1.8. Practice

6.2.1. Poisson Experiment5 min

6.2.2. Poisson Distribution1 min

6.2.3. Example3 min

6.2.4. Practice5 min

6.2.5. Practice5 min

6.3.1. Approximating the Binomial Distribution with Poisson2 min

6.3.2. Example6 min

6.3.3. Practice

7. Continuous Probability Distributions

1.2hr

7.1.1. Continuous Probability Distribution Theory10 min

7.2.1. Normal Distribution11 min

7.2.2. Practice5 min

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

7.3.2. Standardizing a Normal Random Variable4 min

7.3.3. Example10 min

7.3.4. Practice6 min

7.3.5. Practice3 min

7.4.1. Normal Approximation to Binomial2 min

7.4.2. Practice5 min

7.4.3. Normal Approximation to the Binomial Distribution Question4 min

7.4.4. Normal Approximation to the Binomial Distribution Question4 min

8. Sampling Distribution

59min

8.1.1. Sampling Variability & Sampling Distribution12 min

8.2.1. Central Limit Theorem 5 min

8.2.2. Sampling Distribution for a Mean2 min

8.2.3. Example9 min

8.2.4. Sampling Distribution for a Mean Question5 min

8.3.1. Sampling Distribution of Proportions5 min

8.3.2. Example3 min

8.3.3. Sampling Distribution of Proportions4 min

8.4.1. Drawing Samples From a Finite Population8 min

8.4.2. Example4 min

8.4.3. Practice3 min

9. Estimating with Confidence Intervals

48min

9.1.1. Introduction to Confidence Intervals14 min

9.2.1. Confidence Interval for a Mean13 min

9.2.2. Example4 min

9.2.3. Practice3 min

9.3.1. Confidence Interval for a Proportion2 min

9.3.2. Example5 min

9.3.3. Practice4 min

9.4.1. Margin of Error and Sample Size3 min

9.4.2. Practice

10. Hypothesis Testing with One Sample

1.9hr

10.1.1. Introduction to Hypothesis Testing 15 min

10.1.2. Hypothesis Testing Steps25 min

10.2.1. Hypothesis Test for a Mean3 min

10.2.2. Example16 min

10.2.3. Example8 min

10.2.4. Practice4 min

10.3.1. Hypothesis Test for a Proportion10 min

10.3.2. Example4 min

10.3.3. Practice5 min

10.3.4. Practice9 min

10.4.1. Type I and Type II Errors5 min

10.4.2. Type I and Type II Errors1 min

10.4.3. Practice

10.4.4. Practice

10.4.5. Power7 min

10.4.6. Practice

11. Inference for Two Population Means

1.6hr

11.1.1. Comparing Two Independent Means9 min

11.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

11.2.2. Example (Unpooled)11 min

11.2.3. Practice (Unpooled)5 min

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

11.3.2. Example (Pooled)7 min

11.3.3. Practice (Pooled)7 min

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

11.4.2. Confidence Interval for Two Means Containing Zero7 min

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

11.5.1. Confidence Interval Unpooled t2 min

11.5.2. Example: Confidence Interval (Unpooled)5 min

11.5.3. Practice (Unpooled)

11.6.1. Confidence Interval Formula Pooled t2 min

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

11.6.3. Practice (Pooled)

12. Test of Equality of Two Variances

35min

12.1.1. Test of Equality of Two Variances7 min

12.2.1. F-Test for Equality of Two Variances11 min

12.2.2. Example6 min

12.2.3. F-Test for Equality of Two Variances

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

12.3.2. Example7 min

12.3.3. Practice

13. Match Pairs (Dependent Means)

37min

13.1.1. Match Pairs for Dependent Means12 min

13.2.1. Hypothesis Test for Matched Pairs11 min

13.2.2. Example7 min

13.2.3. Practice3 min

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

13.3.2. Practice

14. Inference for Two Population Proportions

49min

14.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

14.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

14.1.3. Example13 min

14.1.4. Practice (Pooled)6 min

14.2.1. Confidence Interval for Differences in Population Proportions3 min

14.2.2. Confidence Interval for Two Proportions1 min

14.2.3. Example4 min

14.2.4. Practice4 min

15. Analysis of Variance

38min

15.1.1. One-Way ANOVA8 min

15.1.2. One-Way ANOVA Table10 min

15.1.3. Example9 min

15.2.1. One-Way ANOVA Hypothesis Test6 min

15.2.2. One-way ANOVA4 min

15.2.3. Practice

16. Scatterplots, Association, and Correlation

37min

16.1.1. Scatterplots5 min

16.1.2. Practice

16.2.1. Correlation5 min

16.2.2. Practice

16.3.1. Solving for Correlation2 min

16.3.2. Example6 min

16.3.3. Practice4 min

16.3.4. Example3 min

16.3.5. Practice

16.4.1. Coefficient of Determination (R Squared)7 min

16.4.2. Assessing Goodness of Fit6 min

16.4.3. Practice

17. Simple Linear Regression

45min

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

17.1.2. Example7 min

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

17.1.4. Practice (Version 1)3 min

17.1.5. Practice (Version 2)5 min

17.1.6. Example5 min

17.2.1. Predictions3 min

17.2.2. Residuals (Errors)5 min

17.2.3. Practice

17.2.4. Residual Plots2 min

17.2.5. Regression Diagnostics 5 min

17.2.6. Practice

17.2.7. Standard Deviation of the Residuals5 min

17.2.8. Practice

18. Inference for Linear Regression

2.2hr

18.1.1. Estimating the Coefficients of the Linear Regression Model9 min

18.1.2. Measures of Variation in Regression9 min

18.1.3. Practice

18.2.1. Standard Error and R Square Formulas7 min

18.2.2. Example5 min

18.2.3. Practice4 min

18.3.1. Confidence Interval for Linear Regression5 min

18.3.2. Example9 min

18.3.3. Practice3 min

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

18.3.5. Practice

18.4.1. Hypothesis Testing for Linear Regression14 min

18.4.2. Example17 min

18.4.3. Example13 min

18.4.4. Practice: Linear Regression Analysis6 min

18.5.1. Prediction Interval of Y7 min

18.5.2. Example12 min

18.5.3. Practice10 min

18.5.4. Practice

19. Multiple Regression

1.7hr

19.1.1. Assessing a Multiple Regression Model5 min

19.1.2. F-test for Multiple Regression5 min

19.1.3. Solving for the F-score9 min

19.1.4. Example2 min

19.1.5. Practice8 min

19.2.1. Hypothesis Testing for Multiple Regression (F-test)7 min

19.2.2. Example13 min

19.2.3. Example26 min

19.2.4. Practice13 min

19.2.5. Practice12 min

Mock Exams

ME.1. Midterm Test 1 - Mock Assessment37 Qns

ME.2. Midterm Test 2 - Mock Assessment26 Qns

ME.3. Final Exam - Mock Assessment27 Qns

Midterm Test 2 Overview

Course Notes

Wizeprep's course notes with hundreds of easy-to-understand explanations, diagrams, and practice problems.

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