COMM 214

Concordia

Course Overview

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Lessons & Practice

I. Welcome

1 min

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. Descriptive Statistics & Analysis (Tabular and Graphical Method)

43min

3. Descriptive Statistics & Analysis (Numerical Methods)

57min

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. Range and Interquartile Range11 min

3.2.2. Variance and Standard Deviation6 min

3.2.3. Practice3 min

3.2.4. Practice3 min

3.2.5. Practice

3.3.1. Percentiles4 min

3.3.2. Example2 min

3.3.3. Practice

3.4.1. Boxplots and Five Number Summary9 min

3.4.2. Practice4 min

3.4.3. Practice

4. Counting Techniques

29min

4.1.1. Fundamental Counting Principle6 min

4.1.2. Permutations and Combinations6 min

4.1.3. Practice1 min

4.1.4. Practice54 sec

4.1.5. More Combination Rules3 min

4.1.6. Example4 min

4.1.7. Practice3 min

4.1.8. Practice

4.2.1. Counting and Probability3 min

4.2.2. Example

4.2.3. Practice1 min

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

5.7.1. Summary of Key Definitions6 min

6. Discrete Random Variables

1.1hr

6.1.1. Discrete Random Variables8 min

6.1.2. Probability Distribution Function4 min

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

6.2.1. Binomial Experiment4 min

6.2.2. Binomial Distribution8 min

7. Continuous Probability Distributions

1.3hr

7.1.1. Continuous Probability Distribution Theory10 min

7.2.1. Uniform Distribution1 min

7.2.2. Practice3 min

7.3.1. Normal Distribution11 min

7.3.2. Practice5 min

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

7.4.2. Standardizing a Normal Random Variable4 min

7.4.3. Example10 min

7.4.4. Practice6 min

7.4.5. Practice3 min

7.5.1. Normal Approximation to Binomial2 min

7.5.2. Practice5 min

7.5.3. Normal Approximation to the Binomial Distribution Question4 min

7.5.4. 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. Type I and Type II Errors5 min

10.2.2. Type I and Type II Errors1 min

10.3.1. Hypothesis Test for a Mean3 min

10.3.2. Example16 min

10.3.3. Example8 min

10.3.4. Practice4 min

10.4.1. Hypothesis Test for a Proportion10 min

10.4.2. Example4 min

10.4.3. Practice5 min

10.4.4. Practice9 min

11. Chi-Square

48min

11.1.1. Types of Chi Square Tests8 min

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

11.1.3. Example7 min

11.1.4. Pratice9 min

11.1.5. Chi-Square Test for Independence5 min

11.1.6. Example8 min

11.1.7. Practice4 min

11.1.8. More on Chi-Square Tests3 min

12. Simple Linear Regression

3hr

12.1.1. Scatterplots5 min

12.1.2. Practice

12.2.1. Correlation5 min

12.2.2. Practice

12.2.3. Solving for Correlation2 min

12.2.4. Example6 min

12.2.5. Practice

12.2.6. Practice4 min

12.2.7. Example3 min

12.3.1. Coefficient of Determination (R Squared)7 min

12.3.2. Assessing Goodness of Fit6 min

12.3.3. Practice

12.4.1. Solving for the Regression Line (Least Square Point Estimates)2 min

12.4.2. Practice (Version 2)5 min

12.4.3. Example5 min

12.5.1. Predictions3 min

12.5.2. Residuals (Errors)5 min

12.5.3. Practice

12.5.4. Residual Plots2 min

12.5.5. Regression Diagnostics 5 min

12.5.6. Practice

12.5.7. Standard Deviation of the Residuals5 min

12.5.8. Practice

12.6.1. Estimating the Coefficients of the Linear Regression Model9 min

12.6.2. Measures of Variation in Regression9 min

12.6.3. Practice

12.7.1. Standard Error and R Square Formulas7 min

12.7.2. Example5 min

12.7.3. Practice4 min

12.8.1. Hypothesis Testing for Linear Regression14 min

12.8.2. Example17 min

12.8.3. Example13 min

12.8.4. Practice: Linear Regression Analysis6 min

12.9.1. Confidence Interval for Linear Regression5 min

12.9.2. Example9 min

12.9.3. Practice3 min

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

12.9.5. Practice

12.10.1. Prediction Interval of Y7 min

12.10.2. Example12 min

12.10.3. Practice10 min

12.10.4. Practice

13. Multiple Regression

1.7hr

13.1.1. Assessing a Multiple Regression Model5 min

13.1.2. F-test for Multiple Regression5 min

13.1.3. Solving for the F-score9 min

13.1.4. Example2 min

13.1.5. Practice8 min

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

13.2.2. Example26 min

13.2.3. Example13 min

13.2.4. Practice13 min

13.2.5. Practice12 min

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Course Notes

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