MATH 1060

Dal

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 Quantitative Data

1.3hr

2.1.1. Histograms4 min

2.1.2. Practice2 min

2.1.3. Practice2 min

2.1.4. Practice

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

2.2.2. Practice3 min

2.3.1. Measures of Central Tendency7 min

2.3.2. Mean and Median Example2 min

2.3.3. Practice

2.3.4. Practice2 min

2.3.5. Practice3 min

2.4.1. Skewness and Symmetry 6 min

2.4.2. Practice

2.5.1. Percentiles4 min

2.5.2. Example2 min

2.5.3. Practice

2.6.1. Range and Interquartile Range11 min

2.6.2. Variance and Standard Deviation6 min

2.6.3. Practice3 min

2.6.4. Practice3 min

2.6.5. Practice

2.7.1. Boxplots and Five Number Summary9 min

2.7.2. Practice4 min

2.7.3. Practice

2.8.1. Summary & Comparing Distributions

2.8.2. Practice

2.8.3. Practice

2.8.4. Practice

2.8.5. Practice

3. Sample Survey

33min

3.1.1. Sample vs. Population7 min

3.1.2. Practice

3.2.1. Statistical Sampling28 sec

3.2.2. Convenience Sampling1 min

3.2.3. Simple Random Sampling3 min

3.2.4. Systematic Sampling2 min

3.2.5. Stratified Sampling vs. Cluster Sampling6 min

3.2.6. Two-Stage Cluster Sampling2 min

3.2.7. Practice

3.2.8. Practice

3.2.9. Practice

3.3.1. Sampling Bias7 min

3.3.2. Recipe for a Good Sample5 min

3.3.3. Practice

3.3.4. Practice

4. Experiments and Observational Studies

23min

4.1.1. Observational Studies4 min

4.1.2. Experimental Studies3 min

4.1.3. Example5 min

4.1.4. Practice

4.2.1. Types of Experimental Designs7 min

4.2.2. Principles of Experimental Design4 min

4.2.4. Practice

4.2.5. Practice

5. Probability

1.9hr

5.1.1. Events & Sample Spaces6 min

5.1.2. Types of Probability6 min

5.1.3. Probability Language & Notation4 min

5.1.4. Example3 min

5.1.5. Independent vs. Mutually Exclusive Events4 min

5.1.6. Example2 min

5.1.7. Practice

5.2.1. Venn Diagrams3 min

5.2.2. Tree Diagrams4 min

5.2.3. Two-way Table5 min

5.3.1. Interpretation of Probability2 min

5.3.2. Complement Rule3 min

5.3.3. Practice1 min

5.3.4. The Addition Rule4 min

5.4.1. Probability of Independent Events4 min

5.4.2. Example3 min

5.4.3. Practice2 min

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

5.5.2. Conditional Probability: Tree Diagram5 min

5.5.3. Bayes’ Theorem4 min

5.5.4. Example4 min

5.5.5. Practice3 min

5.6.1. Example6 min

5.6.2. Example7 min

5.6.3. Example7 min

5.6.4. Practice4 min

5.6.5. Practice5 min

5.7.1. Summary of Key Definitions6 min

6. Random Variables

36min

6.1.1. Discrete Random Variables8 min

6.1.2. Probability Distribution Function4 min

6.1.3. Example4 min

6.1.4. Practice

6.1.5. Practice6 min

6.1.6. Pratice4 min

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

6.2.2. Example5 min

6.2.3. Practice

6.3.1. Linear Combinations of Random Variables

6.3.4. Practice

7. Discrete Probability Distributions

37min

7.1.1. Bernoulli Trials4 min

7.1.2. Practice4 min

7.1.3. Binomial Experiment4 min

7.1.4. Binomial Distribution8 min

7.1.5. Example10 min

7.1.6. Example1 min

7.1.7. Practice6 min

7.1.8. Practice

8. Continuous Probability Distributions & the Normal Model

1.2hr

8.1.1. Continuous Probability Distribution Theory10 min

8.2.1. Normal Distribution11 min

8.2.2. Practice5 min

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

8.3.2. Standardizing a Normal Random Variable4 min

8.3.3. Example10 min

8.3.4. Practice6 min

8.3.5. Practice3 min

8.4.1. Normal Approximation to Binomial2 min

8.4.2. Practice5 min

8.4.3. Normal Approximation to the Binomial Distribution Question4 min

8.4.4. Normal Approximation to the Binomial Distribution Question4 min

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. Sampling Distribution of Proportions4 min

9.4.1. Drawing Samples From a Finite Population8 min

9.4.2. Example4 min

9.4.3. Practice3 min

10. Confidence Interval for Proportions

27min

10.1.1. Introduction to Confidence Intervals14 min

10.2.1. Confidence Interval for a Proportion2 min

10.2.2. Example5 min

10.2.3. Practice4 min

10.3.1. Margin of Error and Sample Size3 min

10.3.2. Practice

11. Hypothesis Testing for Proportions

1.4hr

11.1.1. Introduction to Hypothesis Testing 15 min

11.1.2. Hypothesis Testing Steps25 min

11.2.1. Hypothesis Test for a Proportion10 min

11.2.2. Example4 min

11.2.3. Practice5 min

11.2.4. Practice9 min

11.3.1. Type I and Type II Errors5 min

11.3.2. Type I and Type II Errors1 min

11.3.3. Practice

11.3.4. Practice

11.3.5. Power7 min

11.3.6. Practice

12. Inferences About Means

52min

12.1.1. Confidence Interval for a Mean13 min

12.1.2. Example4 min

12.1.3. Practice3 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

13. Comparing Means

1.6hr

13.1.1. Comparing Two Independent Means9 min

13.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

13.2.2. Example (Unpooled)11 min

13.2.3. Practice (Unpooled)5 min

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

13.3.2. Example (Pooled)7 min

13.3.3. Practice (Pooled)7 min

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

13.4.2. Confidence Interval for Two Means Containing Zero7 min

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

13.5.1. Confidence Interval Unpooled t2 min

13.5.2. Example: Confidence Interval (Unpooled)5 min

13.5.3. Practice (Unpooled)

13.6.1. Confidence Interval Formula Pooled t2 min

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

13.6.3. Practice (Pooled)

14. Paired Samples (Matched Pairs)

37min

14.1.1. Match Pairs for Dependent Means12 min

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

14.2.2. Practice

14.3.1. Hypothesis Test for Matched Pairs11 min

14.3.2. Example7 min

14.3.3. Practice3 min

15. Inference for Two Population Proportions

49min

15.1.1. Hypothesis Testing for Two Independent Population Proportions9 min

15.1.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

15.1.3. Example13 min

15.1.4. Practice (Pooled)6 min

15.2.1. Confidence Interval for Differences in Population Proportions3 min

15.2.2. Confidence Interval for Two Proportions1 min

15.2.3. Example4 min

15.2.4. Practice4 min

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. Practice

16.3.4. Example3 min

16.3.5. Practice4 min

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

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.2 Mock Exam

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