Graphical displays and numerical summaries, data collection methods, probability, sampling distributions, confidence intervals and hypothesis testing involving one or two means and proportions, contingency tables, correlation and simple linear regression.

Course Outline:

Lesson 1: Course Introduction, Syllabus, and Learning Strategies

Lesson 2: The Big Picture in Statistics

Lesson 3: Producing Data–Sampling

Lesson 4: Cautions in Sample Surveys

Lesson 5: Producing Data–Experiments

Lesson 6: Design of Experiments

Lesson 7: Examining Distributions of Quantitative Variables with Graphs

Lesson 8: Examining Distributions with Numerical Measures, Part 1

Lesson 9: Examining Distributions with Numerical Measures, Part 2

Lesson 10: Introduction to Probability

Lesson 11: Random Variables and Probability Distributions

Lesson 12: Normal Probability Distributions and Standard Scores

Lesson 13: The Standard Normal Distribution and Its Applications

Lesson 14: Sampling Distribution of X-Bar and the Central Limit Theorem

Lesson 15: Calculating Probabilities Associated with X-Bar

Lesson 16: Statistical Process Control

Lesson 17: Introduction to Inference

Lesson 18: One-sample t Confidence Interval for Means

Lesson 19: Margin of Error and Sample Size Calculations

Lesson 20: Overview of Hypothesis Testing

Lesson 21: One-sample t-Test for Means

Lesson 22: Hypothesis Testing and Confidence Intervals

Lesson 23: Error Probabilities and Power of a Test–Cautions in Inference

Lesson 24: EDA for Categorical Variables and Sampling Distribution of P-Hat

Lesson 25: One-Sample Z-Confidence Interval for Proportions

Lesson 26: One-Sample Z-Test for Proportions

Lesson 27: Role-Type Classifications; EDA for C to Q Data

Lesson 28: Matched Pairs t Procedures

Lesson 29: Two-sample t Procedures for Means

Lesson 30: Analysis of Variance (ANOVA)

Lesson 31: Two-Way Tables and Conditional Distributions

Lesson 32: Two-sample z-Procedures for Proportions

Lesson 33: Chi-square Test of Independence

Lesson 34: Scatterplots and Correlation

Lesson 35: Linear Regression and r-squared

Lesson 36: Cautions in Correlation and Regression Analysis

Lesson 37: Inference for Slope of Regression Line

Lesson 38: Inference for Regression Predictions: CI and PI

Lesson 2: The Big Picture in Statistics

Lesson 3: Producing Data–Sampling

Lesson 4: Cautions in Sample Surveys

Lesson 5: Producing Data–Experiments

Lesson 6: Design of Experiments

Lesson 7: Examining Distributions of Quantitative Variables with Graphs

Lesson 8: Examining Distributions with Numerical Measures, Part 1

Lesson 9: Examining Distributions with Numerical Measures, Part 2

Lesson 10: Introduction to Probability

Lesson 11: Random Variables and Probability Distributions

Lesson 12: Normal Probability Distributions and Standard Scores

Lesson 13: The Standard Normal Distribution and Its Applications

Lesson 14: Sampling Distribution of X-Bar and the Central Limit Theorem

Lesson 15: Calculating Probabilities Associated with X-Bar

Lesson 16: Statistical Process Control

Lesson 17: Introduction to Inference

Lesson 18: One-sample t Confidence Interval for Means

Lesson 19: Margin of Error and Sample Size Calculations

Lesson 20: Overview of Hypothesis Testing

Lesson 21: One-sample t-Test for Means

Lesson 22: Hypothesis Testing and Confidence Intervals

Lesson 23: Error Probabilities and Power of a Test–Cautions in Inference

Lesson 24: EDA for Categorical Variables and Sampling Distribution of P-Hat

Lesson 25: One-Sample Z-Confidence Interval for Proportions

Lesson 26: One-Sample Z-Test for Proportions

Lesson 27: Role-Type Classifications; EDA for C to Q Data

Lesson 28: Matched Pairs t Procedures

Lesson 29: Two-sample t Procedures for Means

Lesson 30: Analysis of Variance (ANOVA)

Lesson 31: Two-Way Tables and Conditional Distributions

Lesson 32: Two-sample z-Procedures for Proportions

Lesson 33: Chi-square Test of Independence

Lesson 34: Scatterplots and Correlation

Lesson 35: Linear Regression and r-squared

Lesson 36: Cautions in Correlation and Regression Analysis

Lesson 37: Inference for Slope of Regression Line

Lesson 38: Inference for Regression Predictions: CI and PI

Monday–Friday (except holidays)

8:00 a.m.–5:00 p.m. mountain time

Toll-Free: 1-800-914-8931

Local: 801-422-2868

Fax: 801-422-0102

indstudy@byu.edu

Harman Continuing Education Building

770 E University Pkwy

Provo UT 84602

BYU Independent Study

229 HCEB

770 E University Pkwy

Provo UT 84602