STAT*2120

University of Guelph

Course Overview

Lessons & Practice

I. Welcome

1. Sampling and Experiments

1.1hr

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

1.4.1. Observational Studies4 min

1.4.2. Experimental Studies3 min

1.4.3. Example5 min

1.4.4. Practice

1.5.1. Types of Experimental Designs7 min

1.5.2. Principles of Experimental Design4 min

1.5.4. Practice

1.5.5. Practice

2. Probability

1.9hr

2.1.1. Events & Sample Spaces6 min

2.1.2. Types of Probability6 min

2.1.3. Probability Language & Notation4 min

2.1.4. Example3 min

2.1.5. Independent vs. Mutually Exclusive Events4 min

2.1.6. Example2 min

2.1.7. Practice

2.2.1. Venn Diagrams3 min

2.2.2. Tree Diagrams4 min

2.2.3. Two-way Table5 min

2.3.1. Interpretation of Probability2 min

2.3.2. Complement Rule3 min

2.3.3. Practice1 min

2.3.4. The Addition Rule4 min

2.4.1. Probability of Independent Events4 min

2.4.2. Example3 min

2.4.3. Practice2 min

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

2.5.2. Conditional Probability: Tree Diagram5 min

2.5.3. Bayes’ Theorem4 min

2.5.4. Example4 min

2.5.5. Practice3 min

2.6.1. Example6 min

2.6.2. Example7 min

2.6.3. Example7 min

2.6.4. Practice4 min

2.6.5. Practice5 min

2.7.1. Summary of Key Definitions6 min

3. Counting Techniques

29min

3.1.1. Fundamental Counting Principle6 min

3.1.2. Permutations and Combinations6 min

3.1.3. Practice1 min

3.1.4. Practice54 sec

3.1.5. More Combination Rules3 min

3.1.6. Example4 min

3.1.7. Practice3 min

3.1.8. Practice

3.2.1. Counting and Probability3 min

3.2.3. Practice1 min

4. Discrete Random Variables

1.9hr

4.1.1. Discrete Random Variables8 min

4.1.2. Practice

4.1.3. Probability Distribution Function4 min

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

4.1.5. Example5 min

4.1.6. Example4 min

4.1.7. Practice6 min

4.1.8. Practice4 min

4.1.9. Practice

4.2.1. Transforming Data: Shifting & Scaling11 min

4.2.2. Practice2 min

4.2.3. Linear Transformation3 min

4.2.4. Example4 min

4.2.5. Practice2 min

4.3.1. Cumulative Distribution Function (CDF)3 min

4.3.2. Example6 min

4.3.3. Practice2 min

4.4.1. Combining Random Variables7 min

4.4.2. Example2 min

4.4.3. Practice2 min

4.4.4. Example3 min

4.4.5. Practice

4.4.6. Functions of Two Independent Random Variables X and Y5 min

4.4.7. Example3 min

4.4.8. Practice

4.4.9. Practice2 min

4.5.1. Conditional Probability & Joint Distribution7 min

4.5.2. Example5 min

4.5.3. Practice

4.5.4. Random Variables & Joint Distribution7 min

4.5.5. Example3 min

4.5.6. Practice

4.5.8. Practice

6. Continuous Probability Distributions

1.7hr

6.1.1. Continuous Probability Distribution Theory10 min

6.2.1. Uniform Distribution1 min

6.2.2. Practice3 min

6.3.1. Exponential Experiment3 min

6.3.2. Exponential Distribution7 min

6.3.3. Practice7 min

6.4.1. Normal Distribution11 min

6.4.2. Practice5 min

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

6.5.2. Standardizing a Normal Random Variable4 min

6.5.3. Example10 min

6.5.4. Practice6 min

6.5.5. Practice3 min

6.6.1. Normal Approximation to Binomial2 min

6.6.2. Practice5 min

6.6.3. Practice4 min

6.6.4. Practice4 min

6.7.1. Tchebysheff’s Theorem (Chebyshev's Theorem)3 min

6.7.2. Practice2 min

7. Exploratory Data Analysis

49min

7.1.1. Measures of Central Tendency7 min

7.1.2. Mean and Median Example2 min

7.1.3. Practice

7.1.4. Practice2 min

7.1.5. Practice3 min

7.2.1. Skewness and Symmetry 6 min

7.2.2. Practice

7.3.1. Percentiles4 min

7.3.2. Example2 min

7.3.3. Practice

7.4.1. Range and Interquartile Range11 min

7.4.2. Variance and Standard Deviation6 min

7.4.3. Practice3 min

7.4.4. Practice3 min

7.4.5. Practice

8. Descriptive Statistics

35min

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

8.1.2. Practice3 min

8.2.1. Histograms4 min

8.2.2. Practice2 min

8.2.3. Practice2 min

8.2.4. Practice

8.3.1. Boxplots and Five Number Summary9 min

8.3.2. Practice4 min

8.3.3. Practice

8.4.1. Times Series Plots2 min

8.4.2. Practice2 min

8.5.1. Scatterplots5 min

8.5.2. Practice

9. Sampling Distribution

59min

9.1.1. Sampling Variability & Sampling Distribution12 min

9.2.1. Central Limit Theorem 5 min

9.2.2. Sampling Distribution for a Mean2 min

9.2.3. Example9 min

9.2.4. Sampling Distribution for a Mean Question5 min

9.3.1. Sampling Distribution of Proportions5 min

9.3.2. Example3 min

9.3.3. Practice4 min

9.4.1. Drawing Samples From a Finite Population8 min

9.4.2. Example4 min

9.4.3. Practice3 min

10. Estimating with Confidence Intervals

48min

10.1.1. Introduction to Confidence Intervals14 min

10.2.1. Confidence Interval for a Mean13 min

10.2.2. Example4 min

10.2.3. Practice3 min

10.3.1. Confidence Interval for a Proportion2 min

10.3.2. Example5 min

10.3.3. Practice4 min

10.4.1. Margin of Error and Sample Size3 min

10.4.2. Practice

11. Hypothesis Testing with One Sample

1.9hr

11.1.1. Introduction to Hypothesis Testing 15 min

11.1.2. Hypothesis Testing Steps25 min

11.2.1. Hypothesis Test for a Mean3 min

11.2.2. Example16 min

11.2.3. Example8 min

11.2.4. Practice4 min

11.3.1. Hypothesis Test for a Proportion10 min

11.3.2. Example4 min

11.3.3. Practice5 min

11.3.4. Practice9 min

11.4.1. Type I and Type II Errors5 min

11.4.2. Type I and Type II Errors1 min

11.4.3. Practice

11.4.4. Practice

11.4.5. Power7 min

11.4.6. Practice

12. Inference about a Population Variance

41min

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

13. Chi-Square Tests: Goodness of Fit and Contingency Table

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. Inference for Two Population Means

1.6hr

14.1.1. Comparing Two Independent Means9 min

14.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

14.2.2. Example (Unpooled)11 min

14.2.3. Practice (Unpooled)5 min

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

14.3.2. Example (Pooled)7 min

14.3.3. Practice (Pooled)7 min

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

14.4.2. Confidence Interval for Two Means Containing Zero7 min

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

14.5.1. Confidence Interval Unpooled t2 min

14.5.2. Example: Confidence Interval (Unpooled)5 min

14.5.3. Practice (Unpooled)

14.6.1. Confidence Interval Pooled t2 min

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

14.6.3. Practice (Pooled)

15. Match Pairs (Paired t-test for Dependent Means)

37min

15.1.1. Match Pairs for Dependent Means12 min

15.2.1. Hypothesis Test for Matched Pairs11 min

15.2.2. Example7 min

15.2.3. Practice3 min

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

15.3.2. Practice

16. Test of Equality of Two Variances

35min

16.1.1. Test of Equality of Two Variances7 min

16.2.1. F-Test for Equality of Two Variances11 min

16.2.2. Example6 min

16.2.3. F-Test for Equality of Two Variances

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

16.3.2. Example7 min

16.3.3. Practice

17. Inference for Two Population Proportions

49min

17.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

17.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

17.1.3. Example13 min

17.1.4. Practice (Pooled)6 min

17.2.1. Confidence Interval for Differences in Population Proportions3 min

17.2.2. Confidence Interval for Two Proportions1 min

17.2.3. Example4 min

17.2.4. Practice4 min

18. Scatterplots, Association, and Correlation

32min

18.1.1. Correlation5 min

18.1.2. Practice

18.2.1. Solving for Correlation2 min

18.2.2. Example6 min

18.2.3. Practice4 min

18.2.4. Example3 min

18.2.5. Practice

18.3.1. Coefficient of Determination (R Squared)7 min

18.3.2. Assessing Goodness of Fit6 min

18.3.3. Practice

19. Simple Linear Regression

45min

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

19.1.2. Example7 min

19.1.3. Practice (Version 1)3 min

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

19.1.5. Example5 min

19.1.6. Practice (Version 2)5 min

19.2.1. Predictions3 min

19.2.2. Residuals (Errors)5 min

19.2.3. Practice

19.2.4. Residual Plots2 min

19.2.5. Regression Diagnostics 5 min

19.2.6. Practice

19.2.7. Standard Deviation of the Residuals5 min

19.2.8. Practice

20. Inference for Linear Regression

2.2hr

20.1.1. Estimating the Coefficients of the Linear Regression Model9 min

20.1.2. Measures of Variation in Regression9 min

20.1.3. Practice

20.2.1. Standard Error and R Square Formulas7 min

20.2.2. Example5 min

20.2.3. Practice4 min

20.3.1. Confidence Interval for Linear Regression5 min

20.3.2. Example9 min

20.3.3. Practice3 min

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

20.3.5. Practice

20.4.1. Hypothesis Testing for Linear Regression14 min

20.4.2. Example17 min

20.4.3. Example13 min

20.4.4. Practice: Linear Regression Analysis6 min

20.5.1. Prediction Interval of Y7 min

20.5.2. Example12 min

20.5.3. Practice10 min

20.5.4. Practice

21. Analysis of Variance

38min

21.1.1. One-Way ANOVA8 min

21.1.2. One-Way ANOVA Table10 min

21.1.3. Example9 min

21.1.4. Practice

21.2.1. One-Way ANOVA Hypothesis Test6 min

21.2.2. Example4 min

21.2.3. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.1 Mock Exam

medal

Included in Wizeprep Plus

Mock Exam

This mock exam has 21 questions

You must answer all questions before submitting the quiz

Timer

Enabled

mins

Want a tour?