STAT 217

U of C

Course Overview

Lessons & Practice

I. Welcome

1 min

1. Sampling Distribution

59min

1.1.1. Sampling Variability & Sampling Distribution12 min

1.2.1. Central Limit Theorem 5 min

1.2.2. Sampling Distribution for a Mean2 min

1.2.3. Example9 min

1.2.4. Sampling Distribution for a Mean Question5 min

1.3.1. Sampling Distribution of Proportions5 min

1.3.2. Example3 min

1.3.3. Practice4 min

1.4.1. Drawing Samples From a Finite Population8 min

1.4.2. Example4 min

1.4.3. Practice3 min

2. Estimating with Confidence Intervals

1.9hr

2.1.1. Introduction to Confidence Intervals14 min

2.2.1. Confidence Interval for a Mean13 min

2.2.2. Example4 min

2.2.3. Practice3 min

2.3.1. Confidence Interval for a Proportion2 min

2.3.2. Example5 min

2.3.3. Practice4 min

2.4.1. Margin of Error and Sample Size3 min

2.4.2. Practice

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

2.5.2. Confidence Interval for Two Means Containing Zero7 min

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

2.6.1. Confidence Interval Unpooled t2 min

2.6.2. Example: Confidence Interval (Unpooled)5 min

2.6.3. Practice (Unpooled)

2.7.1. Confidence Interval Pooled t2 min

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

2.7.3. Practice (Pooled)

2.8.1. Match Pairs for Dependent Means12 min

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

2.9.2. Practice

2.10.1. Confidence Interval for Differences in Population Proportions3 min

2.10.2. Confidence Interval for Two Proportions1 min

2.10.3. Example4 min

2.10.4. Practice4 min

3. Hypothesis Testing: One Sample

1.9hr

3.1.1. Introduction to Hypothesis Testing 15 min

3.1.2. Hypothesis Testing Steps25 min

3.2.1. Hypothesis Test for a Mean3 min

3.2.2. Example16 min

3.2.3. Example8 min

3.2.4. Practice4 min

3.3.1. Hypothesis Test for a Proportion10 min

3.3.2. Example4 min

3.3.3. Practice5 min

3.3.4. Practice9 min

3.4.1. Type I and Type II Errors5 min

3.4.2. Type I and Type II Errors1 min

4. Hypothesis Testing: Two Samples

1.9hr

4.1.1. Comparing Two Independent Means9 min

4.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

4.2.2. Example (Unpooled)11 min

4.2.3. Practice (Unpooled)5 min

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

4.3.2. Example (Pooled)7 min

4.3.3. Practice (Pooled)7 min

4.4.1. Hypothesis Testing for Two Independent Population Proportions9 min

4.4.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

4.4.3. Example13 min

4.4.4. Practice (Pooled)6 min

4.5.1. Hypothesis Test for Matched Pairs11 min

4.5.2. Example7 min

4.5.3. Practice3 min

5. Scatterplots, Association, and Correlation

37min

5.1.1. Scatterplots5 min

5.1.2. Practice

5.2.1. Correlation5 min

5.2.2. Practice

5.3.1. Solving for Correlation2 min

5.4.1. Coefficient of Determination (R Squared)7 min

5.4.2. Assessing Goodness of Fit6 min

5.4.3. Practice

6. Simple Linear Regression

45min

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

6.1.2. Example7 min

6.1.3. Practice (Version 1)3 min

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

6.1.5. Example5 min

6.1.6. Practice (Version 2)5 min

6.2.1. Predictions3 min

6.2.2. Residuals (Errors)5 min

6.2.3. Practice

6.2.4. Residual Plots2 min

6.2.5. Regression Diagnostics 5 min

6.2.6. Practice

6.2.7. Standard Deviation of the Residuals5 min

6.2.8. Practice

7. Inference for Linear Regression

2.2hr

7.1.1. Estimating the Coefficients of the Linear Regression Model9 min

7.1.2. Measures of Variation in Regression9 min

7.1.3. Practice

7.2.1. Standard Error and R Square Formulas7 min

7.2.2. Example5 min

7.2.3. Practice4 min

7.3.1. Confidence Interval for Linear Regression5 min

7.3.2. Example9 min

7.3.3. Practice3 min

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

7.3.5. Practice

7.4.1. Hypothesis Testing for Linear Regression14 min

7.4.2. Example17 min

7.4.3. Example13 min

7.4.4. Practice: Linear Regression Analysis6 min

7.5.1. Prediction Interval of Y7 min

7.5.2. Example12 min

7.5.3. Practice10 min

7.5.4. Practice

8. Multiple Regression

1.7hr

8.1.1. Assessing a Multiple Regression Model5 min

8.1.2. F-test for Multiple Regression5 min

8.1.3. Solving for the F-score9 min

8.1.4. Example2 min

8.1.5. Practice8 min

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

8.2.2. Example26 min

8.2.3. Example13 min

8.2.4. Practice13 min

8.2.5. Practice12 min

9. Chi-Squared Tests

48min

9.1.1. Types of Chi Square Tests8 min

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

9.1.3. Example7 min

9.1.4. Pratice9 min

9.1.5. Chi-Square Test for Independence5 min

9.1.6. Example8 min

9.1.7. Practice4 min

9.1.8. More on Chi-Square Tests3 min

10. One-Way ANOVA

49min

10.1.1. One-Way ANOVA8 min

10.1.2. One-Way ANOVA Table10 min

10.1.3. Example9 min

10.1.4. Practice

10.2.1. One-Way ANOVA Hypothesis Test6 min

10.2.2. Example4 min

10.2.3. Practice

10.3.1. Post-Hoc Testing: Tukey Test6 min

10.3.2. Post-Hoc Testing: Tukey Test6 min

11. Two-Way ANOVA

19min

11.1.1. Two-Way ANOVA Table8 min

11.1.2. Two-Way ANOVA with Replication Hypothesis Test5 min

11.1.3. Two-Way ANOVA with Replication Hypothesis Test6 min

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

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Answered

Anonymous

Does this cover every topic needed for the final exam? Including combination/permutation, and other small sections?

Lawron L

Instructor

Hello - combination/permutation is found under the 'Counting Rules' chapter. Thank you.

Answered

Liz F

Do you have example questions on how to calculate frequency, relative cumulative frequency, and cumulative relative frequency?

Lawron L

Instructor

Yes, please see the sectiom about Frequency Polygons. 

Notes:
Frequency = counts
Cumulative Frequency = counts accumulated from the minimum 
Relative Cumulative Frequency = % accumulated from the minimum 

Answered

sophia c

do you have a video that helps me understand z scores

Lawron L

Instructor

z scores are introduced in "Continuous Probability Distribution" > "Normal Distributions" and "Standardizing"

Answered

Anonymous

Who came with this concept? 

Jessica Y

Instructor

I don't think one specific person came up with the concept of statistic. It's a very useful branch of math, so I think people saw its application and developed different tools that help us answer important questions :)

Welcome to Wize's Statistics Course!
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