Chevron Left
Вернуться к Linear Regression for Business Statistics

Отзывы учащихся о курсе Linear Regression for Business Statistics от партнера Университет Райса

4.8
звезд
Оценки: 1,273

О курсе

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...

Лучшие рецензии

BB

21 апр. 2020 г.

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

20 дек. 2017 г.

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.

Фильтр по:

26–50 из 202 отзывов о курсе Linear Regression for Business Statistics

автор: Akash v

12 авг. 2021 г.

before this course I know little bit about regression but after doing this I can easily interpreted or predict any data it is very insightful thankyou for this but if you use spss then it will be amazing

автор: Gareth W

1 мар. 2020 г.

A good introduction into the practical uses of regression. It starts with the basics (that you probably learnt at school) and then adds more sophistication that takes the subject up to the current day.

автор: William B

21 дек. 2017 г.

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.

автор: Bhavin B

22 апр. 2020 г.

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.

автор: Himanshu B

20 июня 2020 г.

Great learning with examples from real life, great approach to understand the concept without need to deep dive into the mathematical complexities. A great base to get into Data/Business Analytics.

автор: Shanmugapriya R

20 сент. 2020 г.

It was a very interesting course with a clear explanation of the concepts with practical examples in videos and ppt. This course helped me in understanding the linear regression concepts clearly.

автор: David B

4 окт. 2020 г.

Great course and got quite tricky at the end but its probably I just need to go through a few areas again. Again very clear, very logical, nice pace and plenty of worked examples. Great course.

автор: Flavio E

2 дек. 2019 г.

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.

автор: sushmita d

12 июля 2019 г.

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

автор: Harshit K

20 апр. 2020 г.

By far one of the best courses I have taken online. The simplicity with which the concepts were taught was amazing. There were enough and more exercises to practice the theory too!!

автор: shikha

27 авг. 2019 г.

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.

автор: Santiago R R

13 авг. 2020 г.

A very complex last quiz in comparison with the others, truly serves as a skill-checker, without directly asking about a lot of topics. Loved the course, thank you!

автор: Dr. M K

16 мая 2020 г.

It is a well designed course on regression analysis. I would like to recommend this course to all research scholars who are going to use regression in their study.

автор: Isabel C R

5 апр. 2020 г.

Great course! Very well explained by a knowledgeable instructor. The only issue is that the sound of some of the videos is very low even after I increase volume.

автор: Miranda W

1 мая 2018 г.

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.

автор: Dibyajyoti D

19 авг. 2020 г.

Needless to say one of the best courses on Linear Regression. I have just one complain we could have atleast explored the math a bit if not apply it directly.

автор: Jitka S

6 мар. 2020 г.

Excellent course, same as the previous courses of this specialization. Explains statistic for beginners in a great way, easy to follow, with a lot of examples.

автор: Lluís M

9 дек. 2017 г.

Really useful for understanding regressions, the meaning of the coefficients. Also very helpful to do more analysis than what most people usually do to data.

автор: Victor W

20 апр. 2019 г.

Very good course for people of all backgrounds and experience levels in the topic! If you are new to regression or familiar with it I highly recommend it.

автор: Ryan M

10 апр. 2017 г.

Well taught and extremely useful information. I was able to take knowledge from this course and apply it directly to analytical reports I write at work.

автор: Renier B

12 мар. 2020 г.

Very hands-on without losing sight of theory behind it, so one knows how it works, why it works and maybe most important when to use it and when not.

автор: RAMASUBRAMANIYAM S

20 окт. 2018 г.

Completion of the four courses in the specialization makes me feel more interested and confident in the vast art of Business Statistics and Analytics

автор: Saurav K

22 июня 2020 г.

Its a wonderful course and all the concept has been covered and it is highly recommended to a person who wants to pursue career in business analyst.

автор: Bonnie A K

8 окт. 2021 г.

Excellent, easy to follow presentation of materials. Good explanations, reasonable pace. Very helpful for understanding concepts and applications.

автор: JUBIN K S

3 июня 2020 г.

Beautiful course. Thank you Coursera for providing us this platform to learn and interact with the promising faculty of a prestigious university.