Statway College w/ Corequisite 4.1

Statway College with Corequisite Modules 1-5
1.1: Setting Course Expectations and Creating Productive Classroom Norms
1.1-S: Understanding Percentages
1.2 The Statistical Analysis Process
1.2-S: Using Percentages to Explore Climate Data
Growth Mindset Activity 1.3
Questions: You Can Grow Your Brain
1.3: Research Questions and Types of Statistical Studies
1.3-S: Evaluating and Simplifying Expressions
1.4: Random Sampling & Experiments 
1.5: Sampling Strategies, Bias, and Random Assignment in Experiments
2.1: Distributions of Quantitative Data—Dotplots & Histograms
2.2: Quantifying the Center of a Distribution—Sample Mean and Sample Median
2.2-S: Measures of Center
2.3: Quantifying Variability Relative to the Median
2.3-S: Boxplots & Outliers
2.4: Quantifying Variability Relative to the Mean 
2.4 tress Reappraisal
2.4-S: Standard Deviation
Preparation 3.1 
3.1: Scatterplots
3.1-SA: Scatterplots (Supplement A) 
3.1-S: Scatterplots
3.2: Linear Correlation
3.3: Lines of Best Fit 
3.4: Residuals and the Line of Best Fit 
3.4-S: The Line of Best Fit 287 
3.5: The Coefficient of Determination 
3.5-S: The Coefficient of Determination 
3.6: Correlation Inference
3.6-S: Inferences in Linear Correlation 
4.1: Investigating Patterns and Exponential Models 
Preparation 5.1
5.1: Introduction to Probabilities
5.1-S: Probabilities and Long-Term Behavior
5.2: Probability Types and Probability Rules 
5.3: Two-Way Tables, Proportions, and Probabilities
5.3-S: Using Simulations to Estimate probabilities
5.4: Probability Distributions of Discrete Random Variables
5.4-S: Discrete Probability Distributions
5.5: The Binomial Distribution
5.6: Probability Distributions of Continuous Random Variable
5.6-S: More Probability Distribution
5.7: The Normal Distribution and Z-scores 
5.7-S:What’s Normal? 
5.8: The Standard Normal Distribution
5.8-S: Applications of Normal Distributions

Statway College with Corequisite Modules 6-10
Preparation 6.1 
6.1: Sampling Distributions of Sample Proportions
6.1-S: Parameters & Statistics
6.2: Confidence Intervals for a Population Proportion
6.2-S: Constructing Confidence Intervals
6.3: Hypothesis Tests for a Population Proportion 1
6.3-S: Testing Claims about Population Parameters
6.4: Hypothesis Tests for a Population Proportion
6.4-S: Hypothesis Tests for a Population Proportion
6.5: Hypothesis Tests for a Population Proportion
7.1: Distributions of Differences Between Sample Proportions
7.1-S: Distributions of Differences Between Sample Proportions
7.2: Testing for Differences Between Population Proportions
7.2-S: Testing for Differences Between Population Proportions 
8.1-S(A): Normal Distributions of Quantitative Data 
Preparation 8.1
8.1: Acorn Mass Table (Supplement)
8.1: Sampling Distributions of Sample Means
8.1S-B: Central Limit Theorem for Sample Means 
Preparation 8.2
8.2: Confidence Intervals for a Population Mean
8.2-S: T-Distributions & Interval Estimates for Means
8.3: Confidence Intervals for Paired Samples
8.4: Hypothesis Tests for Population Means 1
8.4-S: Inference on Quantitative Data
8.5: Hypothesis Tests for Population Means 2 
8.6: Hypothesis Tests for Paired Samples
8.6-S: Hypothesis Tests for Paired Samples
8.7: Distributions of Differences Between Sample Means
8.8: Testing for Differences Between Population Means
8.8-S: Testing for Differences Between Population Means
8.9: Summary of Inference Methods 
8.9-S: Summary of Inference Methods
Preparation 8.10 
8.10: One-Way ANOVA: Equal Sample Sizes 
8.11: One-Way ANOVA: Unequal Sample Sizes 
9.1: The Chi-Square Distribution
9.1-S: The Chi-Square Distribution 
9.2: Goodness of Fit 
9.2-S: Goodness of Fit
9.3: Testing for Independence with Two-Way Tables
9.3-S: Testing for Independence with Two-Way Tables
9.4: The Chi-Square Test for Homogeneity in Two-Way Tables
9.4-S: The Chi-Square Test for Homogeneity
10.1: Statistical Models, Mathematical Functions, and Linear Functions
10.2: Solving Linear Equations 
10.3: More Linear Equations
10.4: Proportionality
10.5: Linear Models–Answering Various Types of Questions Algebraically
10.6: Inequalities
10.7: Multiple Representations of Exponential Models 
10.8: Power Models