COMM 215

Concordia

Course Overview

Lessons & Practice

I. Welcome

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. Probability

1.9hr

4.1.1. Events & Sample Spaces6 min

4.1.2. Types of Probability6 min

4.1.3. Probability Language & Notation4 min

4.1.4. Example3 min

4.1.5. Independent vs. Mutually Exclusive Events4 min

4.1.6. Example2 min

4.1.7. Practice

4.2.1. Venn Diagrams3 min

4.2.2. Tree Diagrams4 min

4.2.3. Two-way Table5 min

4.3.1. Interpretation of Probability2 min

4.3.2. Complement Rule3 min

4.3.3. Practice1 min

4.3.4. The Addition Rule4 min

4.4.1. Probability of Independent Events4 min

4.4.2. Example3 min

4.4.3. Practice2 min

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

4.5.2. Conditional Probability: Tree Diagram5 min

4.5.3. Bayes’ Theorem4 min

4.5.4. Example4 min

4.5.5. Practice3 min

4.6.1. Example6 min

4.6.2. Example7 min

4.6.3. Example7 min

4.6.4. Practice4 min

4.6.5. Practice5 min

4.7.1. Summary of Key Definitions6 min

5. Discrete Random Variables

1.1hr

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. Example4 min

5.1.5. Example5 min

5.1.6. Practice

5.1.7. Pratice4 min

5.1.8. Practice6 min

5.1.9. Practice

5.2.1. Binomial Experiment4 min

5.2.2. Binomial Distribution8 min

5.2.3. Example10 min

5.2.4. Example1 min

5.2.5. Practice6 min

5.2.6. Practice

6. Continuous Probability Distributions

1.3hr

6.1.1. Continuous Probability Distribution Theory10 min

6.2.1. Uniform Distribution1 min

6.2.2. Practice3 min

6.3.1. Normal Distribution11 min

6.3.2. Practice5 min

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

6.4.2. Standardizing a Normal Random Variable4 min

6.4.3. Example10 min

6.4.4. Practice6 min

6.4.5. Practice3 min

6.5.1. Normal Approximation to Binomial2 min

6.5.2. Practice5 min

6.5.3. Normal Approximation to the Binomial Distribution Question4 min

6.5.4. Normal Approximation to the Binomial Distribution Question4 min

7. Sampling Distribution

59min

7.1.1. Sampling Variability & Sampling Distribution12 min

7.2.1. Central Limit Theorem 5 min

7.2.2. Sampling Distribution for a Mean2 min

7.2.3. Example9 min

7.2.4. Sampling Distribution for a Mean Question5 min

7.3.1. Sampling Distribution of Proportions5 min

7.3.2. Example3 min

7.3.3. Sampling Distribution of Proportions4 min

7.4.1. Drawing Samples From a Finite Population8 min

7.4.2. Example4 min

7.4.3. Practice3 min

8. Estimating with Confidence Intervals

48min

8.1.1. Introduction to Confidence Intervals14 min

8.2.1. Confidence Interval for a Mean13 min

8.2.2. Example4 min

8.2.3. Practice3 min

8.3.1. Confidence Interval for a Proportion2 min

8.3.2. Example5 min

8.3.3. Practice4 min

8.4.1. Margin of Error and Sample Size3 min

8.4.2. Practice

9. Hypothesis Testing with One Sample

1.9hr

9.1.1. Introduction to Hypothesis Testing 15 min

9.1.2. Hypothesis Testing Steps25 min

9.2.1. Type I and Type II Errors5 min

9.2.2. Type I and Type II Errors1 min

9.2.3. Practice

9.2.4. Practice

9.2.5. Power7 min

9.2.6. Practice

9.3.1. Hypothesis Test for a Mean3 min

9.3.2. Example16 min

9.3.3. Example8 min

9.3.4. Practice4 min

9.4.1. Hypothesis Test for a Proportion10 min

9.4.2. Example4 min

9.4.3. Practice5 min

9.4.4. Practice9 min

10. Chi-Square

48min

10.1.1. Types of Chi Square Tests8 min

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

10.1.3. Example7 min

10.1.4. Pratice9 min

10.1.5. Chi-Square Test for Independence5 min

10.1.6. Example8 min

10.1.7. Practice4 min

10.1.8. More on Chi-Square Tests3 min

11. Simple Linear Regression

3hr

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

11.1.2. Practice (Version 2)5 min

11.1.3. Example5 min

11.2.1. Correlation5 min

11.2.2. Practice

11.2.3. Solving for Correlation2 min

11.2.4. Example6 min

11.2.5. Practice

11.2.6. Practice4 min

11.2.7. Example3 min

11.3.1. Coefficient of Determination (R Squared)7 min

11.3.2. Assessing Goodness of Fit6 min

11.3.3. Practice

11.4.1. Predictions3 min

11.4.2. Residuals (Errors)5 min

11.4.3. Practice

11.4.4. Residual Plots2 min

11.4.5. Regression Diagnostics 5 min

11.4.6. Practice

11.4.7. Standard Deviation of the Residuals5 min

11.4.8. Practice

11.5.1. Estimating the Coefficients of the Linear Regression Model9 min

11.5.2. Measures of Variation in Regression9 min

11.5.3. Practice

11.6.1. Standard Error and R Square Formulas7 min

11.6.2. Example5 min

11.6.3. Practice4 min

11.7.1. Hypothesis Testing for Linear Regression14 min

11.7.2. Example17 min

11.7.3. Example13 min

11.7.4. Practice: Linear Regression Analysis6 min

11.8.1. Confidence Interval for Linear Regression5 min

11.8.2. Example9 min

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

11.8.4. Practice3 min

11.8.5. Practice

11.9.1. Prediction Interval of Y7 min

11.9.2. Example12 min

11.9.3. Practice10 min

11.9.4. Practice

12. Multiple Regression

1.7hr

12.1.1. Assessing a Multiple Regression Model5 min

12.1.2. F-test for Multiple Regression5 min

12.1.3. Solving for the F-score9 min

12.1.4. Example2 min

12.1.5. Practice8 min

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

12.2.2. Example26 min

12.2.3. Example13 min

12.2.4. Practice13 min

12.2.5. Practice12 min

Mock Exams

ME.1. Midterm Examination - Mock Assessment26 Qns

ME.2. Final Examination - Mock Assessment42 Qns

ME.1 Midterm Examination - Mock Assessment

medal

Included in Wizeprep Plus

Midterm Examination - Mock Assessment

This mock exam has 24 questions

You must answer all questions before submitting the quiz

Timer

Enabled

mins

Want a tour?