Statistics: Regression Analysis Using Excel

Statistics: Regression Analysis Using Excel, available at $59.99, has an average rating of 4.3, with 14 lectures, 4 quizzes, based on 41 reviews, and has 880 subscribers.

You will learn about Use Excel to quantify relationships within data Use data to predict quantifiable outcomes Incorporate seasonality into predictions Measure the strength of the relationship between one or more independent and one dependent variable This course is ideal for individuals who are Beginning statisticians It is particularly useful for Beginning statisticians.

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Summary

Title: Statistics: Regression Analysis Using Excel

Price: $59.99

Average Rating: 4.3

Number of Lectures: 14

Number of Quizzes: 4

Number of Published Lectures: 13

Number of Published Quizzes: 4

Number of Curriculum Items: 18

Number of Published Curriculum Objects: 17

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Use Excel to quantify relationships within data
Use data to predict quantifiable outcomes
Incorporate seasonality into predictions
Measure the strength of the relationship between one or more independent and one dependent variable

Who Should Attend

Beginning statisticians

Target Audiences

Beginning statisticians

Regression is an important statistical tool. Using regression, we can detect and quantify relationships within a data set. For example, you have a data set of truck distances driven and stops made. Using this information, we can construct an equation which allows prediction of duration given distance number of stops. This would be of great use to anyone having to give out quotations.

I show you how to check whether your regression actually works and how accurate it is.

Indicator or ‘dummy’ variables are an important source of information, and I show you how to convert textual data into dummy variables for inclusion in the regression analysis. We know how long repair jobs take and months since last service. Does including information about whether the job was electrical or mechanical make predicted repair time any more accurate?

Sales go up at certain seasons: being able to measure those increases and predict them is highly useful.

We also cover elasticity, a topic often missed out in regression courses. Using elasticity, we can predict the effect on sales volume in precent of a percent change in selling price.

I provide detailed explanations and provide the datasets so that you can follow along.

The pace of the course is measured and step by step, each section building on the last. The datasets I use in the examples are included so that you can run your own regressions and compare results.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Why do regression anyway?

Lecture 2: Measuring the degree of correlation between two variables

Chapter 2: Defining the regression equation

Lecture 1: Defining the regression equation

Chapter 3: The method of least squares

Lecture 1: The method of least squares

Chapter 4: Loading Data Analysis

Lecture 1: Loading Data Analysis

Chapter 5: Running a regression

Lecture 1: Running a regression

Chapter 6: Accuracy and Significance

Lecture 1: Accuracy and Significance

Chapter 7: Adding more variables

Lecture 1: Improving accuracy by adding variables

Chapter 8: Price elasticity

Lecture 1: Price elasticity

Chapter 9: The indicator variable

Lecture 1: Using an indicator or 'dummy' variable to include categorical data

Chapter 10: Linear trends and time

Lecture 1: Linear trends and time

Chapter 11: Seasonality

Lecture 1: Capturing seasonal effects using dummy variables

Chapter 12: Checking the assumptions

Lecture 1: Checking the assumptions

Instructors

Stephen Peplow
Statistics instructor at a Canadian University

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 8 votes
4 stars: 9 votes
5 stars: 24 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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