STAT 263

Queen's

Course Overview

Grade Boosters

Lessons & Practice

I. Welcome

2. Summarizing Data: Listing and Grouping

32min

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

2.1.2. Practice3 min

2.2.1. Histograms4 min

2.2.2. Practice2 min

2.2.3. Practice2 min

2.2.4. Practice

2.3.1. Bar Chart3 min

2.3.2. Practice

2.4.1. Frequency Polygons2 min

2.4.2. Practice4 min

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

2.5.2. Simpson’s Paradox3 min

2.5.3. Practice

2.6.1. Pie Chart3 min

2.6.2. Practice

3. Summarizing Data: Measures of Location

39min

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. Percentiles4 min

3.2.2. Example2 min

3.2.3. Practice

3.3.1. Boxplots and Five Number Summary9 min

3.3.2. Practice4 min

3.3.3. Practice

3.4.1. Skewness and Symmetry 6 min

3.4.2. Practice

4. Summarizing Data: Measures of Variation

28min

4.1.1. Range and Interquartile Range11 min

4.1.2. Variance and Standard Deviation6 min

4.1.3. Practice3 min

4.1.4. Practice3 min

4.1.5. Practice

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

4.2.2. Practice2 min

5. Possibilities and Probabilities

29min

5.1.1. Fundamental Counting Principle6 min

5.1.2. Permutations and Combinations6 min

5.1.3. Practice1 min

5.1.4. Practice54 sec

5.1.5. More Combination Rules3 min

5.1.6. Example4 min

5.1.7. Practice3 min

5.1.8. Practice

5.2.1. Counting and Probability3 min

5.2.3. Practice1 min

6. Some Rules of Probability

1.9hr

6.1.1. Events & Sample Spaces6 min

6.1.2. Types of Probability6 min

6.1.3. Probability Language & Notation4 min

6.1.4. Example3 min

6.1.5. Independent vs. Mutually Exclusive Events4 min

6.1.6. Example2 min

6.1.7. Practice

6.2.1. Venn Diagrams3 min

6.2.2. Tree Diagrams4 min

6.2.3. Two-way Table5 min

6.3.1. Interpretation of Probability2 min

6.3.2. Complement Rule3 min

6.3.3. Practice1 min

6.3.4. The Addition Rule4 min

6.4.1. Probability of Independent Events4 min

6.4.2. Example3 min

6.4.3. Practice2 min

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

6.5.2. Conditional Probability: Tree Diagram5 min

6.5.3. Bayes’ Theorem4 min

6.5.4. Example4 min

6.5.5. Practice3 min

6.6.1. Example6 min

6.6.2. Example7 min

6.6.3. Example7 min

6.6.4. Practice4 min

6.6.5. Practice5 min

6.7.1. Summary of Key Definitions6 min

7. Expectations and Decisions

36min

7.1.1. Discrete Random Variables8 min

7.1.2. Probability Distribution Function4 min

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

7.1.4. Example5 min

7.1.5. Example4 min

7.1.6. Practice

7.1.7. Practice6 min

7.1.8. Pratice4 min

7.1.9. Practice

8. Probability Distributions

1.2hr

8.1.1. Binomial Experiment4 min

8.1.2. Binomial Distribution8 min

8.1.3. Example10 min

8.1.4. Example1 min

8.1.5. Practice6 min

8.1.6. Practice

8.2.1. Hypergeometric Experiment5 min

8.2.2. Hypergeometric Distribution9 min

8.2.3. Example4 min

8.2.4. Practice4 min

8.2.5. Practice Question

8.3.1. Poisson Experiment5 min

8.3.2. Poisson Distribution1 min

8.3.3. Example3 min

8.3.4. Practice5 min

8.3.5. Practice5 min

9. The Normal Distribution

1.3hr

9.1.1. Continuous Probability Distribution Theory10 min

9.2.1. Normal Distribution11 min

9.2.2. Practice5 min

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

9.3.2. Standardizing a Normal Random Variable4 min

9.3.3. Example10 min

9.3.4. Practice6 min

9.3.5. Practice3 min

9.4.1. Normal Approximation to Binomial2 min

9.4.2. Practice5 min

9.4.3. Normal Approximation to the Binomial Distribution Question4 min

9.4.4. Normal Approximation to the Binomial Distribution Question4 min

9.5.1. Chebyshev's Theorem3 min

9.5.2. Practice2 min

10. Sampling and Sampling Distributions

59min

10.1.1. Sampling Variability & Sampling Distribution12 min

10.2.1. Central Limit Theorem 5 min

10.2.2. Sampling Distribution for a Mean2 min

10.2.3. Example9 min

10.2.4. Sampling Distribution for a Mean Question5 min

10.3.1. Sampling Distribution of Proportions5 min

10.3.2. Example3 min

10.3.3. Sampling Distribution of Proportions4 min

10.4.1. Drawing Samples From a Finite Population8 min

10.4.2. Example4 min

10.4.3. Practice3 min

11. Estimating with Confidence Intervals

48min

11.1.1. Introduction to Confidence Intervals14 min

11.2.1. Confidence Interval for a Mean13 min

11.2.2. Example4 min

11.2.3. Practice3 min

11.3.1. Confidence Interval for Population Variance

11.3.2. Confidence Interval for Population Variance

11.4.1. Confidence Interval for a Proportion2 min

11.4.2. Example5 min

11.4.3. Practice4 min

11.5.1. Margin of Error and Sample Size3 min

11.5.2. Practice

12. Tests of Hypotheses: Means

4hr

12.1.1. Introduction to Hypothesis Testing 15 min

12.1.2. Hypothesis Testing Steps25 min

12.2.1. Hypothesis Test for a Mean3 min

12.2.2. Example16 min

12.2.3. Example8 min

12.2.4. Practice4 min

12.3.1. Type I and Type II Errors5 min

12.3.2. Type I and Type II Errors1 min

12.3.3. Practice

12.3.4. Practice

12.3.5. Power7 min

12.3.6. Practice

12.4.1. Comparing Two Independent Means9 min

12.4.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

12.5.2. Example (Unpooled)11 min

12.5.3. Practice (Unpooled)5 min

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

12.6.2. Example (Pooled)7 min

12.6.3. Practice (Pooled)7 min

12.7.1. Confidence Interval Unpooled t2 min

12.7.2. Example: Confidence Interval (Unpooled)5 min

12.7.3. Practice (Unpooled)

12.8.1. Confidence Interval Formula Pooled t2 min

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

12.8.3. Practice (Pooled)

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

12.9.2. Confidence Interval for Two Means Containing Zero7 min

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

12.10.1. Match Pairs for Dependent Means12 min

12.11.1. Hypothesis Test for Matched Pairs11 min

12.11.2. Example7 min

12.11.3. Practice3 min

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

12.12.2. Practice

13. Tests of Hypotheses: Variance (Standard Deviation)

20min

13.1.1. Hypothesis Test for Population Variance8 min

13.1.2. Example8 min

13.1.3. Hypothesis Test for Population Variance

13.1.4. Practice4 min

14. Tests of Hypotheses: Based on Count Data

2.1hr

14.1.1. Hypothesis Test for a Proportion10 min

14.1.2. Example4 min

14.1.3. Practice5 min

14.1.4. Practice9 min

14.2.1. Hypothesis Testing for Two Independent Population Proportions9 min

14.2.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

14.2.3. Example13 min

14.2.4. Practice (Pooled)6 min

14.3.1. Confidence Interval for Differences in Population Proportions3 min

14.3.2. Confidence Interval for Two Proportions1 min

14.3.3. Example4 min

14.3.4. Practice4 min

14.4.1. Chi-Square Distribution

14.5.1. Types of Chi Square Tests8 min

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

14.5.3. Example7 min

14.5.4. Pratice9 min

14.5.5. Chi-Square Test for Independence5 min

14.5.6. Example8 min

14.5.7. Practice4 min

14.5.8. More on Chi-Square Tests3 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

15.2.4. One-way ANOVA16 Qns

16. Simple Linear Regression

2.3hr

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

16.1.2. Example7 min

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

16.1.4. Practice (Version 1)3 min

16.1.5. Practice (Version 2)5 min

16.1.6. Example5 min

16.2.1. Predictions3 min

16.2.2. Residuals (Errors)5 min

16.2.3. Practice

16.2.4. Residual Plots2 min

16.2.5. Regression Diagnostics 5 min

16.2.6. Practice

16.2.7. Practice

16.2.8. Standard Deviation of the Residuals5 min

16.3.1. Estimating the Coefficients of the Linear Regression Model9 min

16.3.2. Measures of Variation in Regression9 min

16.3.3. Practice

16.4.1. Confidence Interval for Linear Regression5 min

16.4.2. Example9 min

16.4.3. Practice3 min

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

16.4.5. Practice

16.5.1. Hypothesis Testing for Linear Regression14 min

16.5.2. Example17 min

16.5.3. Example13 min

16.5.4. Practice: Linear Regression Analysis6 min

17. Scatterplots, Association, and Correlation

53min

17.1.1. Scatterplots5 min

17.1.2. Practice

17.2.1. Correlation5 min

17.2.2. Practice

17.3.1. Solving for Correlation2 min

17.3.2. Example6 min

17.3.3. Practice

17.3.4. Example3 min

17.3.5. Practice4 min

17.4.1. Coefficient of Determination (R Squared)7 min

17.4.2. Assessing Goodness of Fit6 min

17.4.3. Practice

17.5.1. Standard Error and R Square Formulas7 min

17.5.2. Example5 min

17.5.3. Practice4 min

Mock Exams

ME.1. Term Test - Mock Assessment35 Qns

ME.2. Final Exam - Mock Assessment40 Qns

ME.2 Final Exam - Mock Assessment

medal

Included in Wizeprep Plus

Crash Course

Term Test Crash Course

D

Daniel L

0 secs

Releases: May 25, 9:24pm

Final Exam - Mock Assessment

This mock exam has 40 questions

You must answer all questions before submitting the quiz

Timer

Enabled

mins

Want a tour?