# 学生对 莱斯大学 提供的 Linear Regression for Business Statistics 的评价和反馈

4.8
588 个评分
93 个审阅

## 课程概述

Regression Analysis is perhaps the single most important Business Statistics tool used in the industry. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. This is the fourth course in the specialization, "Business Statistics and Analysis". The course introduces you to the very important tool known as Linear Regression. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects. All these are introduced and explained using easy to understand examples in Microsoft Excel. The focus of the course is on understanding and application, rather than detailed mathematical derivations. Note: This course uses the ‘Data Analysis’ tool box which is standard with the Windows version of Microsoft Excel. It is also standard with the 2016 or later Mac version of Excel. However, it is not standard with earlier versions of Excel for Mac. WEEK 1 Module 1: Regression Analysis: An Introduction In this module you will get introduced to the Linear Regression Model. We will build a regression model and estimate it using Excel. We will use the estimated model to infer relationships between various variables and use the model to make predictions. The module also introduces the notion of errors, residuals and R-square in a regression model. Topics covered include: • Introducing the Linear Regression • Building a Regression Model and estimating it using Excel • Making inferences using the estimated model • Using the Regression model to make predictions • Errors, Residuals and R-square WEEK 2 Module 2: Regression Analysis: Hypothesis Testing and Goodness of Fit This module presents different hypothesis tests you could do using the Regression output. These tests are an important part of inference and the module introduces them using Excel based examples. The p-values are introduced along with goodness of fit measures R-square and the adjusted R-square. Towards the end of module we introduce the ‘Dummy variable regression’ which is used to incorporate categorical variables in a regression. Topics covered include: • Hypothesis testing in a Linear Regression • ‘Goodness of Fit’ measures (R-square, adjusted R-square) • Dummy variable Regression (using Categorical variables in a Regression) WEEK 3 Module 3: Regression Analysis: Dummy Variables, Multicollinearity This module continues with the application of Dummy variable Regression. You get to understand the interpretation of Regression output in the presence of categorical variables. Examples are worked out to re-inforce various concepts introduced. The module also explains what is Multicollinearity and how to deal with it. Topics covered include: • Dummy variable Regression (using Categorical variables in a Regression) • Interpretation of coefficients and p-values in the presence of Dummy variables • Multicollinearity in Regression Models WEEK 4 Module 4: Regression Analysis: Various Extensions The module extends your understanding of the Linear Regression, introducing techniques such as mean-centering of variables and building confidence bounds for predictions using the Regression model. A powerful regression extension known as ‘Interaction variables’ is introduced and explained using examples. We also study the transformation of variables in a regression and in that context introduce the log-log and the semi-log regression models. Topics covered include: • Mean centering of variables in a Regression model • Building confidence bounds for predictions using a Regression model • Interaction effects in a Regression • Transformation of variables • The log-log and semi-log regression models...

## 热门审阅

##### WB

Dec 21, 2017

I have found Course 3 and 4 of this specialization to be challenging, but rewarding. It has helped me build confidence that I can do just about anything with data provided to increase positive impact.

##### SD

Jul 12, 2019

I learned a lot.I gain confidence in analyzing data in Excel.I am happy that I have successfully completed it with simple understanding given on each topic.It was great help.Thank you very much

## 51 - Linear Regression for Business Statistics 的 75 个评论（共 88 个）

Apr 26, 2019

practical

Nov 17, 2019

This was the most useful and insightful class in the specialization so far, at least for me and what I was looking to get out of these courses

Nov 21, 2019

Had a better understanding on regression.

Sep 12, 2019

Thoroughly explained Linear regression in very simple format.

Sep 14, 2019

Mr. Bodle presents the material in a very organized and understandable fashion. Well worth the time taking this class.

Dec 03, 2019

Curso muito bom, aprendi muitos conceitos, o curso é bastante voltado para interpretação dos resultados, fiz algumas analises no trabalho aplicando os conceitos que aprendi, recomendo bastante.

Aug 28, 2019

Very informative, well designed course. The flow of the course was set in such a way that you easily cruise through it. Thoroughly enjoyed learning. Highly recommended.

Sep 17, 2017

excellent content.

Jun 21, 2017

Somewhat hard for some part. But practice makes prefect

Apr 17, 2018

Excellently explained!

Feb 21, 2018

Very useful course, thank you!

May 01, 2018

Well structured course with clear modules and helpful exercises to reinforce the material. Professor Borle does a great job and is very responsive to questions.

Jun 21, 2018

Good course, examples are very constructive and instructor presentations are vey good

Jul 14, 2019

Extraordinary course! Great presentations, great contents, usefull exercises and applications

Aug 26, 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

Jul 05, 2018

very east to understand and quick to learn. strong recommendation!

Aug 01, 2018

Excellent introduction to Linear Regression. As you progress, you learn how to use dummy (category) variables as well as interaction variables. Examples are explained in detail so you can understand how it works. This course isn't about understanding all the detailed math & theory, but explains enough to you understand (at a high level) what you're doing and why. Then, you learn how to do it in Excel. I really enjoyed this class!

Oct 06, 2019

I thoroughly enjoyed this course. The instructors were very clear and concise thereby making the course easy to follow and understand.

Aug 08, 2018

Rigorous and rewarding when you put the work in.

Apr 13, 2017

An in depth explanation of how to use Excel for Linear Regression and what the Output values in Excel's Regression mean. Note that the transcripts/subtitles contain many errors, which can be problematical for the hard of hearing or non English speakers, which is why I gave the course only 4 points.

Dec 28, 2017

I thought it was very well done but I felt like the material was kind of rushed and some subjects were brushed over. I would like a little more in depth coverage of this subject.

Jun 06, 2018

Phenomenal course. A little more in-depth explanations and more examples for the concepts introduced in the last two weeks would have been nice though. In week 3 and 4, I found it challenging to go so quickly over so many new concepts all of a sudden. But still, I would really recommend taking this course, I found it useful.

Dec 18, 2017

That would be better if the correct answer if being shown after passing the exam, because I can't able to learn from my mistakes

Great course !!!

Jan 17, 2018

The explanations of a lot of interpretations are repetitive.

Apr 01, 2018

Really liked the course!!!