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

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1,100 个评分
183 条评论

## 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

BB
Apr 21, 2020

Wonderful Course having in depth knowledge about all the topics of regression analysis. Instructor is very much clear about the topic and having good teaching skill. Method of teaching also very good.

WB
Dec 20, 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.

## 51 - Linear Regression for Business Statistics 的 75 个评论（共 179 个）

Aug 1, 2018

I loved this course and the videos and lecture were clearly explained. Doing the Regression model was a whole new experience for me!

May 16, 2017

Well designed and business friendly explanation. Thanks to Sharad Borle I gained much deeper knowledge on linear regression.

Sep 14, 2019

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

Oct 13, 2020

Amazing, I learn how to use Microsoft Excel and Linear Regression, that is a useful subject in business. Thanks a lot.

Oct 18, 2018

The course is essential for those who have no background in linear regression. The Lecturer of this course is amazing.

Aug 9, 2020

Excellent course. Gives great insight about regression and it's application. Must do course for any business analyst.

Aug 10, 2017

give a glimpse of regression without math/stats , suit for those who purely focus on LR application in business area

Oct 13, 2020

Very good teacher. I've learned a lot. The quizzes were just at the right difficulty to measure what you've learned

Jan 15, 2020

Good to learn and gain understanding on Linear regression model , dummy variable as well as log transformation.

Apr 18, 2020

Excellent course for anyone aiming to build a strong understanding of regression and building relevant models.

May 26, 2020

it as a great course and the main point the simplification for all business cases and how to learn the tricks

Mar 16, 2019

Marvellous course! Gives a very good idea of linear regression. A must for students and practicing managers.

Aug 26, 2017

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

Sep 23, 2020

the course is worth it!! this data analytics can be made so comfortable, was commendable. full points

Oct 11, 2017

Very well designed and good examples illustrate the Regression model. Thanks for the Opportunity,

May 19, 2020

Excellent content, Easy to understand examples, Interesting practice quizzes, Great Professor..!

Apr 17, 2020

very well formulated and EXCELLENTLY explained by sir and great overall team effort. Thank you.

Jul 14, 2019

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

Apr 29, 2017

Excellent course! Very clear explanations of concepts and lots of great examples.

Recommended!

Jan 18, 2018

Very well structured course. Sharad is an excellent teacher. Learnt a lot from this course.

May 20, 2020

A well informative course would like to revise this course again as it is very helpful.

Apr 3, 2020

loved learning from the course. It seemed easy in application after learning so well!

Jun 20, 2018

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

Jan 24, 2018

extemely lucid and connecting course with ample real time excel hands on and example

May 31, 2020

Fundamentals are explained beautifully with very good examples and easy explanation