STAT 201

SFU

Course Overview

Lessons & Practice

I. Welcome

1 min

1. Getting Started & Picturing Distributions with Graphs

1hr

2. Describing Distributions with Numbers

1hr

2.1.1. Measures of Central Tendency7 min

2.1.2. Mean and Median Example2 min

2.1.3. Practice

2.1.4. Practice2 min

2.1.5. Practice3 min

2.2.1. Skewness and Symmetry 6 min

2.2.2. Practice

2.3.1. Percentiles4 min

2.3.2. Example2 min

2.3.3. Practice

2.4.1. Range and Interquartile Range11 min

2.4.2. Variance and Standard Deviation6 min

2.4.3. Practice3 min

2.4.4. Practice3 min

2.4.5. Practice

2.5.1. Boxplots and Five Number Summary9 min

2.5.2. Practice4 min

2.5.3. Practice

3. The Normal Distributions

1.2hr

3.1.1. Continuous Probability Distribution Theory10 min

3.2.1. Normal Distribution11 min

3.2.2. Practice5 min

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

3.3.2. Standardizing a Normal Random Variable4 min

3.3.3. Example10 min

3.3.4. Practice6 min

3.3.5. Practice3 min

3.4.1. Normal Approximation to Binomial2 min

3.4.2. Practice5 min

3.4.3. Practice4 min

3.4.4. Practice4 min

4. Scatterplots and Correlation

37min

4.1.1. Scatterplots5 min

4.1.2. Practice

4.2.1. Correlation5 min

4.2.2. Practice

4.3.1. Solving for Correlation2 min

4.4.1. Coefficient of Determination (R Squared)7 min

4.4.2. Assessing Goodness of Fit6 min

4.4.3. Practice

5. Regression

45min

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

5.1.2. Example7 min

5.1.3. Practice (Version 1)3 min

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

5.1.5. Example5 min

5.1.6. Practice (Version 2)5 min

5.2.1. Predictions3 min

5.2.2. Residuals (Errors)5 min

5.2.3. Practice

5.2.4. Residual Plots2 min

5.2.5. Regression Diagnostics 5 min

5.2.6. Practice

5.2.7. Standard Deviation of the Residuals5 min

5.2.8. Practice

6. Two-Way Tables

7min

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

6.1.2. Simpson’s Paradox3 min

6.1.3. Practice

7. Skip

8. Producing Data: Sampling

26min

8.1.1. Sampling Bias7 min

8.1.2. Recipe for a Good Sample5 min

8.1.3. Practice

8.1.4. Practice

8.2.1. Statistical Sampling28 sec

8.2.2. Convenience Sampling1 min

8.2.3. Simple Random Sampling3 min

8.2.4. Systematic Sampling2 min

8.2.5. Stratified Sampling vs. Cluster Sampling6 min

8.2.6. Two-Stage Cluster Sampling2 min

8.2.7. Practice

8.2.8. Practice

8.2.9. Practice

9. Producing Data: Experiments

12min

9.1.1. Observational Studies4 min

9.1.2. Experimental Studies3 min

9.1.3. Example5 min

9.1.4. Practice

10. Skip

11. Skip

12. Introducing Probability

1.9hr

12.1.1. Events & Sample Spaces6 min

12.1.2. Types of Probability6 min

12.1.3. Probability Language & Notation4 min

12.1.4. Example3 min

12.1.5. Independent vs. Mutually Exclusive Events4 min

12.1.6. Example2 min

12.1.7. Practice

12.2.1. Venn Diagrams3 min

12.2.2. Tree Diagrams4 min

12.2.3. Two-way Table5 min

12.3.1. Interpretation of Probability2 min

12.3.2. Complement Rule3 min

12.3.3. Practice1 min

12.3.4. The Addition Rule4 min

12.4.1. Probability of Independent Events4 min

12.4.2. Example3 min

12.4.3. Practice2 min

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

12.5.2. Conditional Probability: Tree Diagram5 min

12.5.3. Bayes’ Theorem4 min

12.5.4. Example4 min

12.5.5. Practice3 min

12.6.1. Example6 min

12.6.2. Example7 min

12.6.3. Example7 min

12.6.4. Practice4 min

12.6.5. Practice5 min

12.7.1. Summary of Key Definitions6 min

13. Skip

14. Binomial Distributions

37min

14.1.1. Bernoulli Trials4 min

14.1.2. Practice4 min

14.1.3. Binomial Experiment4 min

14.1.4. Binomial Distribution8 min

14.1.5. Example10 min

14.1.6. Example1 min

14.1.7. Practice6 min

14.1.8. Practice

15. Sampling Distributions

59min

15.1.1. Sampling Variability & Sampling Distribution12 min

15.2.1. Central Limit Theorem 5 min

15.2.2. Sampling Distribution for a Mean2 min

15.2.3. Example9 min

15.2.4. Sampling Distribution for a Mean Question5 min

15.3.1. Sampling Distribution of Proportions5 min

15.3.2. Example3 min

15.3.3. Practice4 min

15.4.1. Drawing Samples From a Finite Population8 min

15.4.2. Example4 min

15.4.3. Practice3 min

16. Confidence Intervals: The Basics

37min

16.1.1. Introduction to Confidence Intervals14 min

16.2.1. Confidence Interval for a Mean13 min

16.2.2. Example4 min

16.2.3. Practice3 min

16.3.1. Margin of Error and Sample Size3 min

16.3.2. Practice

17. Tests of Significance: The Basics

1.4hr

17.1.1. Introduction to Hypothesis Testing 15 min

17.1.2. Hypothesis Testing Steps25 min

17.2.1. Hypothesis Test for a Mean3 min

17.2.2. Example16 min

17.2.3. Example8 min

17.2.4. Practice4 min

17.3.1. Type I and Type II Errors5 min

17.3.2. Type I and Type II Errors1 min

18. Skip

19. Skip

20. Inference about a Population Mean

37min

20.1.1. Match Pairs for Dependent Means12 min

20.2.1. Hypothesis Test for Matched Pairs11 min

20.2.2. Example7 min

20.2.3. Practice3 min

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

20.3.2. Practice

21. Comparing Two Means

1.6hr

21.1.1. Comparing Two Independent Means9 min

21.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

21.2.2. Example (Unpooled)11 min

21.2.3. Practice (Unpooled)5 min

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

21.3.2. Example (Pooled)7 min

21.3.3. Practice (Pooled)7 min

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

21.4.2. Confidence Interval for Two Means Containing Zero7 min

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

21.5.1. Confidence Interval Unpooled t2 min

21.5.2. Example: Confidence Interval (Unpooled)5 min

21.5.3. Practice (Unpooled)

21.6.1. Confidence Interval Pooled t2 min

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

21.6.3. Practice (Pooled)

22. Inference about a Population Proportion

39min

22.1.1. Confidence Interval for a Proportion2 min

22.1.2. Example5 min

22.1.3. Practice4 min

22.2.1. Hypothesis Test for a Proportion10 min

22.2.2. Example4 min

22.2.3. Practice5 min

22.2.4. Practice9 min

23. Comparing Two Proportions

49min

23.1.1. Confidence Interval for Differences in Population Proportions3 min

23.1.2. Confidence Interval for Two Proportions1 min

23.1.3. Example4 min

23.1.4. Practice4 min

23.2.1. Hypothesis Testing for Two Independent Population Proportions9 min

23.2.2. Hypothesis Test Steps: Comparing Two Independent Proportions8 min

23.2.3. Example13 min

23.2.4. Practice (Pooled)6 min

24. Skip

25. Categorical Variables: The Chi-Square Test

48min

25.1.1. Types of Chi Square Tests8 min

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

25.1.3. Example7 min

25.1.4. Pratice9 min

25.1.5. Chi-Square Test for Independence5 min

25.1.6. Example8 min

25.1.7. Practice4 min

25.1.8. More on Chi-Square Tests3 min

26. Inference for Regression

2.2hr

26.1.1. Estimating the Coefficients of the Linear Regression Model9 min

26.1.2. Measures of Variation in Regression9 min

26.1.3. Practice

26.2.1. Standard Error and R Square Formulas7 min

26.2.2. Example5 min

26.2.3. Practice4 min

26.3.1. Confidence Interval for Linear Regression5 min

26.3.2. Example9 min

26.3.3. Practice3 min

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

26.3.5. Practice

26.4.1. Hypothesis Testing for Linear Regression14 min

26.4.2. Example17 min

26.4.3. Example13 min

26.4.4. Practice: Linear Regression Analysis6 min

26.5.1. Prediction Interval of Y7 min

26.5.2. Example12 min

26.5.3. Practice10 min

26.5.4. Practice

27. One-Way Analysis of Variance: Comparing Several Means

38min

27.1.1. One-Way ANOVA8 min

27.1.2. One-Way ANOVA Table10 min

27.1.3. Example9 min

27.1.4. Practice

27.2.1. One-Way ANOVA Hypothesis Test6 min

27.2.2. Example4 min

27.2.3. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

ME.4. Midterm Exam - Mock Assessment39 Qns

ME.5. Final Exam - Mock Assessment37 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!
My name is Lawron and I'm here to help you ace your course! Feel free to go through this resource at your own pace
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