STAT 151

U of A

Course Overview

Lessons & Practice

I. Welcome

1. Intro to Stats

18min

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

3. Displaying & Summarizing Categorical Data

20min

3.1.1. Pie Chart3 min

3.1.2. Practice

3.2.1. Bar Chart3 min

3.2.2. Practice

3.3.1. Segmented Bar Chart (or Stacked Columns)3 min

3.3.2. Practice4 min

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

3.4.2. Simpson’s Paradox3 min

3.4.3. Practice

4. Displaying & Summarizing Quantitative Data

1.5hr

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

4.1.2. Practice3 min

4.2.1. Histograms4 min

4.2.2. Practice2 min

4.2.3. Practice2 min

4.2.4. Practice

4.3.1. Measures of Central Tendency7 min

4.3.2. Mean and Median Example2 min

4.3.3. Practice

4.3.4. Practice2 min

4.3.5. Practice3 min

4.4.1. Skewness and Symmetry 6 min

4.4.2. Practice

4.5.1. Range and Interquartile Range11 min

4.5.2. Variance and Standard Deviation6 min

4.5.3. Practice3 min

4.5.4. Practice3 min

4.5.5. Practice

4.6.1. Percentiles4 min

4.6.2. Example2 min

4.6.3. Practice

4.7.1. Boxplots and Five Number Summary9 min

4.7.2. Practice4 min

4.7.3. Practice

4.8.1. 👉Summary + Comparing Distributions3 min

4.8.2. Practice: Comparing Histograms Based on Distribution2 min

4.8.3. Practice: Comparing Box Plots2 min

4.8.4. Practice: Comparing Mean and Standard Deviation2 min

4.8.5. Practice: Making Decisions Based on Center & Spread2 min

4.9.1. Transforming Data

4.9.2. Practice: Transforming Data

5. Density Curve & Normal Model

1hr

5.1.1. Continuous Probability Distribution Theory10 min

5.2.1. Normal Distribution11 min

5.2.2. Practice5 min

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

5.3.2. Standardizing a Normal Random Variable4 min

5.3.3. Example10 min

5.3.4. Practice6 min

5.3.5. Practice3 min

6. 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. Counting Techniques

29min

7.1.1. Fundamental Counting Principle6 min

7.1.2. Permutations and Combinations6 min

7.1.3. Practice1 min

7.1.4. Practice54 sec

7.1.5. More Combination Rules3 min

7.1.6. Example4 min

7.1.7. Practice3 min

7.1.8. Practice

7.2.1. Counting and Probability3 min

7.2.3. Practice1 min

8. Discrete Random Variables

58min

8.1.1. Discrete Random Variables8 min

8.1.2. Probability Distribution Function4 min

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

8.1.4. Example5 min

8.1.5. Example4 min

8.1.6. Practice

8.1.7. Practice6 min

8.1.8. Pratice4 min

8.1.9. Practice

8.2.1. Transforming Data: Shifting & Scaling11 min

8.2.2. Practice2 min

8.2.3. Linear Transformation3 min

8.2.4. Example4 min

8.2.5. Practice2 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. Inference About a Proportion - Confidence Intervals

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. Inference About a Proportion -- Hypothesis Testing

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. Comparing Two Proportions

49min

12.1.1. Confidence Interval for Differences in Population Proportions3 min

12.1.2. Confidence Interval for Two Proportions1 min

12.1.3. Example4 min

12.1.4. Practice4 min

12.2.1. Hypothesis Testing for Two Independent Population Proportions9 min

12.2.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

12.2.3. Example13 min

12.2.4. Practice (Pooled)6 min

13. Chi-Square

48min

13.1.1. Types of Chi Square Tests8 min

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

13.1.3. Example7 min

13.1.4. Practice9 min

13.1.5. Chi-Square Test for Independence5 min

13.1.6. Example8 min

13.1.7. Practice4 min

13.1.8. More on Chi-Square Tests3 min

14. Inference About a Mean -- Confidence Intervals

20min

14.1.1. Confidence Interval for a Mean13 min

14.1.2. Example4 min

14.1.3. Practice3 min

15. Inference About a Mean -- Hypothesis Testing

32min

15.1.1. Hypothesis Test for a Mean3 min

15.1.2. Example16 min

15.1.3. Example8 min

15.1.4. Practice4 min

16. Comparing Two Means

2.2hr

16.1.1. Comparing Two Independent Means9 min

16.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

16.2.2. Example (Unpooled)11 min

16.2.3. Practice (Unpooled)5 min

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

16.3.2. Example (Pooled)7 min

16.3.3. Practice (Pooled)7 min

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

16.4.2. Confidence Interval for Two Means Containing Zero7 min

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

16.5.1. Confidence Interval Unpooled t2 min

16.5.2. Example: Confidence Interval (Unpooled)5 min

16.5.3. Practice (Unpooled)

16.6.1. Confidence Interval Formula Pooled t2 min

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

16.6.3. Practice (Pooled)

16.7.1. Match Pairs for Dependent Means12 min

16.8.1. Hypothesis Test for Matched Pairs11 min

16.8.2. Example7 min

16.8.3. Practice3 min

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

16.9.2. Practice

17. Analysis of Variance

38min

17.1.1. One-Way ANOVA8 min

17.1.2. One-Way ANOVA Table10 min

17.1.3. Example9 min

17.2.1. One-Way ANOVA Hypothesis Test6 min

17.2.2. One-way ANOVA4 min

17.2.3. Practice

17.2.4. One-way ANOVA16 Qns

18. Scatterplots, Association, and Correlation

37min

18.1.1. Scatterplots5 min

18.1.2. Practice

18.2.1. Correlation5 min

18.2.2. Practice

18.3.1. Solving for Correlation2 min

18.3.2. Example6 min

18.3.3. Practice4 min

18.3.4. Example3 min

18.3.5. Practice

18.4.1. Coefficient of Determination (R Squared)7 min

18.4.2. Assessing Goodness of Fit6 min

18.4.3. Practice

19. Simple Linear Regression

34min

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

19.1.2. Example7 min

19.1.3. Practice (Version 1)3 min

19.2.1. Predictions3 min

19.2.2. Residuals (Errors)5 min

19.2.3. Practice

19.2.4. Residual Plots2 min

19.2.5. Regression Diagnostics 5 min

19.2.6. Practice

19.2.7. Standard Deviation of the Residuals5 min

19.2.8. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.4. Midterm Exam - Mock Assessment36 Qns

ME.5. Final Exam - Mock Assessment51 Qns

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Answered

n

neve b

How do u love stats🥲 it’s cutting my souls 

L

Lawron L

Instructor

Statistics exists everywhere: in business, in research, in politics, in sports, etc. I suppose I'm lucky to be really good at stats. Like all students, I have weaknesses in courses like English and Accounting that cut my soul. I'm also a terrible singer. Now I'm sharing my stats skills to help other students like yourself. 

Answered

Kieran M

How much does this cost

L

Lawron L

Instructor

Thank you for your interest! Please email [email protected]

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