STP 226

ASU

Course Overview

Lessons & Practice

I. Welcome

1. Collecting Data & Sampling [1.1-1.2, 2.1]

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. Displaying & Summarizing Categorical Data [2.2-2.3]

20min

2.1.1. Pie Chart3 min

2.1.2. Practice

2.2.1. Bar Chart3 min

2.2.2. Practice

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

2.3.2. Practice4 min

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

2.4.2. Simpson’s Paradox3 min

2.4.3. Practice

3. Displaying & Summarizing Quantitative Data [2.2-2.3]

28min

3.1.1. Histograms4 min

3.1.2. Practice2 min

3.1.3. Practice2 min

3.1.4. Practice

3.2.1. Dot Plots5 min

3.2.2. Practice

3.3.1. Frequency Polygons2 min

3.3.2. Practice4 min

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

3.4.2. Practice3 min

3.5.1. Times Series Plots2 min

3.5.2. Practice2 min

4. Distribution Shape, Measures of Center and Variation [2.4, 3.1-3.2]

49min

4.1.1. Measures of Central Tendency7 min

4.1.2. Mean and Median Example2 min

4.1.3. Practice

4.1.4. Practice2 min

4.1.5. Practice3 min

4.2.1. Skewness and Symmetry 6 min

4.2.2. Practice

4.3.1. Percentiles4 min

4.3.2. Example2 min

4.3.3. Practice

4.4.1. Range and Interquartile Range11 min

4.4.2. Variance and Standard Deviation6 min

4.4.3. Practice3 min

4.4.4. Practice3 min

4.4.5. Practice

5. Boxplots [3.4]

14min

5.1.1. Boxplots and Five Number Summary9 min

5.1.2. Practice4 min

5.1.3. Practice

6. Experiments and Observational Studies

23min

6.1.1. Observational Studies4 min

6.1.2. Experimental Studies3 min

6.1.3. Example5 min

6.1.4. Practice

6.2.1. Types of Experimental Designs7 min

6.2.2. Principles of Experimental Design4 min

6.2.4. Practice

6.2.5. Practice

7. Probability [5.1-5.3]

1.9hr

7.1.1. Events & Sample Spaces6 min

7.1.2. Types of Probability6 min

7.1.3. Probability Language & Notation4 min

7.1.4. Example3 min

7.1.5. Independent vs. Mutually Exclusive Events4 min

7.1.6. Example2 min

7.1.7. Practice

7.2.1. Venn Diagrams3 min

7.2.2. Tree Diagrams4 min

7.2.3. Two-way Table5 min

7.3.1. Interpretation of Probability2 min

7.3.2. Complement Rule3 min

7.3.3. Practice1 min

7.3.4. The Addition Rule4 min

7.4.1. Probability of Independent Events4 min

7.4.2. Example3 min

7.4.3. Practice2 min

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

7.5.2. Conditional Probability: Tree Diagram5 min

7.5.3. Bayes’ Theorem4 min

7.5.4. Example4 min

7.5.5. Practice3 min

7.6.1. Example6 min

7.6.2. Example7 min

7.6.3. Example7 min

7.6.4. Practice4 min

7.6.5. Practice5 min

7.7.1. Summary of Key Definitions6 min

8. Discrete Random Variables & Probability Distributions [5.4, 5.5]

3hr

8.1.1. Discrete Random Variables8 min

8.1.2. Practice

8.1.3. Probability Distribution Function4 min

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

8.1.5. Example5 min

8.1.6. Example4 min

8.1.7. Practice6 min

8.1.8. Practice4 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

8.3.1. Cumulative Distribution Function (CDF)3 min

8.3.2. Example6 min

8.3.3. Practice2 min

8.4.1. Combining Random Variables7 min

8.4.2. Example2 min

8.4.3. Practice2 min

8.4.4. Example3 min

8.4.5. Practice

8.4.6. Functions of Two Independent Random Variables X and Y5 min

8.4.7. Example3 min

8.4.8. Practice

8.4.9. Practice2 min

8.5.1. Conditional Probability & Joint Distribution7 min

8.5.2. Example5 min

8.5.3. Practice

8.5.4. Random Variables & Joint Distribution7 min

8.5.5. Example3 min

8.5.6. Practice

8.5.8. Practice

8.6.1. Bernoulli Trials4 min

8.6.2. Practice4 min

8.6.3. Binomial Experiment4 min

8.6.4. Binomial Distribution8 min

8.6.5. Example10 min

8.6.6. Example1 min

8.6.7. Practice6 min

8.6.8. Practice

8.7.1. Poisson Experiment5 min

8.7.2. Poisson Distribution1 min

8.7.3. Example3 min

8.7.4. Practice5 min

8.7.5. Practice5 min

8.8.1. Approximating the Binomial Distribution with Poisson2 min

8.8.2. Example6 min

8.8.3. Practice

8.9.1. Hypergeometric Experiment5 min

8.9.2. Hypergeometric Distribution9 min

8.9.3. Example4 min

8.9.4. Practice4 min

8.9.5. Practice Question

9. Continuous Probability Distributions [6.1-6.3]

1.4hr

9.1.1. Continuous Probability Distribution Theory10 min

9.2.1. Uniform Distribution1 min

9.2.2. Practice3 min

9.3.1. Normal Distribution11 min

9.3.2. Practice5 min

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

9.4.2. Standardizing a Normal Random Variable4 min

9.4.3. Example10 min

9.4.4. Practice6 min

9.4.5. Practice3 min

9.5.1. Normal Approximation to Binomial2 min

9.5.2. Practice5 min

9.5.3. Practice4 min

9.5.4. Practice4 min

9.6.1. Tchebysheff’s Theorem (Chebyshev's Theorem)3 min

9.6.2. Practice2 min

10. Sampling Distribution [7.1-7.3]

59min

10.1.1. Sampling Variability & Sampling Distribution12 min

10.2.1. Central Limit Theorem 5 min

10.2.2. Sampling Distribution for a Mean2 min

10.2.3. Example9 min

10.2.4. Sampling Distribution for a Mean Question5 min

10.3.1. Sampling Distribution of Proportions5 min

10.3.2. Example3 min

10.3.3. Practice4 min

10.4.1. Drawing Samples From a Finite Population8 min

10.4.2. Example4 min

10.4.3. Practice3 min

11. Confidence Intervals for One Population Mean[8.1-8.4]

37min

11.1.1. Introduction to Confidence Intervals14 min

11.2.1. Confidence Interval for a Mean13 min

11.2.2. Example4 min

11.2.3. Practice3 min

11.3.1. Margin of Error and Sample Size3 min

11.3.2. Practice

12. Hypothesis Testing with One Sample [9.1-9.5]

1.4hr

12.1.1. Introduction to Hypothesis Testing 15 min

12.1.2. Hypothesis Testing Steps25 min

12.2.1. Hypothesis Test for a Mean3 min

12.2.2. Example16 min

12.2.3. Example8 min

12.2.4. Practice4 min

12.3.1. Type I and Type II Errors5 min

12.3.2. Type I and Type II Errors1 min

12.3.3. Practice

12.3.4. Practice

12.3.5. Power7 min

12.3.6. Practice

13. Inference for Two Independent Population Means [10.3]

1.6hr

13.1.1. Comparing Two Independent Means9 min

13.1.2. Hypothesis Test Steps: Comparing Two Independent Means11 min

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

13.2.2. Example (Unpooled)11 min

13.2.3. Practice (Unpooled)5 min

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

13.3.2. Example (Pooled)7 min

13.3.3. Practice (Pooled)7 min

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

13.4.2. Confidence Interval for Two Means Containing Zero7 min

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

13.5.1. Confidence Interval Unpooled t2 min

13.5.2. Example: Confidence Interval (Unpooled)5 min

13.5.3. Practice (Unpooled)

13.6.1. Confidence Interval Pooled t2 min

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

13.6.3. Practice (Pooled)

14. Inferences for Two Dependent Population Means [10.4]

37min

14.1.1. Match Pairs for Dependent Means12 min

14.2.1. Hypothesis Test for Matched Pairs11 min

14.2.2. Example7 min

14.2.3. Practice3 min

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

14.3.2. Practice

15. Confidence Interval and Hypothesis Test for One Population Proportion [11.1-11.2]

39min

15.1.1. Confidence Interval for a Proportion2 min

15.1.2. Example5 min

15.1.3. Practice4 min

15.2.1. Hypothesis Test for a Proportion10 min

15.2.2. Example4 min

15.2.3. Practice5 min

15.2.4. Practice9 min

16. Chi-Square [12.1-12.2, 12.4]

48min

16.1.1. Types of Chi Square Tests8 min

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

16.1.3. Example7 min

16.1.4. Pratice9 min

16.1.5. Chi-Square Test for Independence5 min

16.1.6. Example8 min

16.1.7. Practice4 min

16.1.8. More on Chi-Square Tests3 min

17. Linear Correlation [4.1-4.4]

1.4hr

17.1.1. Scatterplots5 min

17.1.2. Practice

17.2.1. Correlation5 min

17.2.2. Practice

17.2.3. Solving for Correlation2 min

17.2.4. Example6 min

17.2.5. Practice4 min

17.2.6. Example3 min

17.2.7. Practice

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

17.3.2. Example7 min

17.3.3. Practice (Version 1)3 min

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

17.3.5. Example5 min

17.3.6. Practice (Version 2)5 min

17.4.1. Predictions3 min

17.4.2. Residuals (Errors)5 min

17.4.3. Practice

17.4.4. Residual Plots2 min

17.4.5. Regression Diagnostics 5 min

17.4.6. Practice

17.4.7. Standard Deviation of the Residuals5 min

17.4.8. Practice

17.5.1. Coefficient of Determination (R Squared)7 min

17.5.2. Assessing Goodness of Fit6 min

17.5.3. Practice

Mock Exams

ME.1. Mock Exam21 Qns

ME.2. Mock Exam18 Qns

ME.3. Mock Exam27 Qns

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Welcome to Wize's Statistics Course!
My name is Lawron and I'm here to help you ace STP 226! This course has video tutorials and practice questions that cover most topics you will learn in STP 226. Feel free to go through this resource at your own pace
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