BUS204: Linear Regression | Saylor Academy

STAGE - Never been refreshed - Debugging On

Watch this lecture, which discusses how to interpret and understand a linear regression and how regression equations enable you to make predictions.

Source: Philip Stark, https://www.youtube.com/watch?v=O-Rb2yeofTY
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Last modified: Friday, October 15, 2021, 9:24 AM

Course Introduction

Course Syllabus

Unit 1: Introduction to Statistical Analysis

1.1: Why Do We Need to Study Statistical Analysis as Part of a Business Program?

Why Do We Need to Study Statistical Analysis as Part of a Business Program?

1.2: Measuring Data

Definitions of Statistics, Probability, and Key Terms

Kinds of Data in Statistics

1.3: Measures of Spread and Data

Variance and Standard Deviation

Descriptive Statistics

1.4: Spreadsheet Exercises: Measures of Central Tendency and Spread

Measures of Central Tendency: Mode, Median, Mean, and Midrange

Practice: Measures of Middle and Spread

1.5: Spreadsheet Exercises: Graphs of Histograms and Frequency Tables

Graphs and Charts

Shapes of Distributions

Unit 1 Problem Set and Assessment

Descriptive Statistics Homework

Unit 1 Assessment

Unit 2: Counting, Probability, and Probability Distributions

2.1: Counting

Terminology

Counting and Probability

2.2: Theories of Probability

Independent and Mutually Exclusive Events

Venn Diagrams

2.3: Set Theory

Probability with Playing Cards and Venn Diagrams

Addition Rule for Probability

Two Basic Rules of Probability

Set Theory

2.4: Probability Fundamentals

Properties of Continuous Probability Density Functions

Probability Fundamentals

2.5: Probability Distributions and the Binomial Distribution

Probability Density Functions and Random Variables

Discrete Random Variables

Probability Distributions

Unit 2 Problem Set and Assessment

Probability Homework

Discrete Random Variables Homework

Unit 2 Assessment

Unit 3: The Normal Distribution

3.1: The Normal Distribution

Qualitative Sense of Normal Distributions

The Central Limit Theorem

3.2: Practice Problems

Normal Distribution Problems: Z-score

More Empirical Rule and Z-score Practice

Unit 3 Problem Set and Assessment

Practice: The Normal Distribution

Unit 3 Assessment

Unit 4: Sampling and Sampling Distributions

4.1: Sampling and Sampling Distributions

Sampling Distribution of the Sample Mean

Calculating the Sample Size n: Continuous and Binary Random Variables

Sampling and Sampling Distributions

Unit 4 Problem Set and Assessment

Sampling and Data Homework

Unit 4 Assessment

Unit 5: Estimation and Hypothesis Testing

5.1: Estimation and Confidence Intervals

Confidence Intervals

Confidence Intervals and Estimating Parameters

Computing Confidence Intervals

5.2: Hypothesis Testing

Hypothesis Testing and P-values

Hypothesis Testing with One Sample

Hypothesis Testing

5.3: Testing Equality of Two Percentages

Comparing Population Proportions

Hypothesis Testing with Two Samples

Hypothesis Testing

5.4: The Chi-Squared Test for Goodness of Fit

Introduction to the Chi-Square Distribution

The Chi-Square Distribution

Unit 5 Problem Set and Assessment

Confidence Intervals Homework

Unit 5 Assessment