Вернуться к Linear Regression for Business Statistics

4.8

Оценки: 554

•

Рецензии: 87

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...

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.

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

Фильтр по:

автор: Shady N S T

•Dec 27, 2018

I love this Specialization, and look forward to completing it! It's an amazing journey in Statistics with Excel! If you're a beginner in Statistics, you might see the whole Specialization a bit difficult and will need to look for a Statistics course. The instructor is also a huge plus!

автор: Rishav k

•Dec 26, 2017

Could have been more challenging. Moderate courses are easy to pass but doesn't bring about extreme competitive spirit. Some peer graded assignments could be better.

автор: Nazmus S S

•Jan 30, 2019

VERY GOOD COURSE. Professor is great

автор: Padmapriyadarshini

•Jan 03, 2019

Excellent course! added a lot to my understanding

автор: ARVIND K S

•Mar 16, 2019

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

автор: shubhangi P M

•Mar 20, 2019

Thanks S

автор: MONTCHO H M

•Jul 25, 2018

interesting course

автор: Miranda W

•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.

автор: Kirtana S

•May 07, 2017

I thoroughly enjoyed this course. This is an excellent course for all those who wish to understand and apply regression at work. Professor Borle explains every concept in detail and ensures he interprets each aspect as simple as possible.

автор: Andrew B

•Sep 17, 2017

Easy to understand and apply

автор: Li Y

•Jun 21, 2017

Somewhat hard for some part. But practice makes prefect

автор: Chinmay P

•Mar 19, 2018

The detailing of the course was really good! :)

автор: Siddharth S

•Jan 18, 2018

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

автор: William B

•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.

автор: Avi G

•Sep 20, 2017

A very good course on Regression statistics with examples from the business sector that can be used later in work or life. Prof. Borle explained all topics slowly and clearly. i would extend the course to more Regression topics (residuals@ more)

Thank you prof. Borle.

автор: jorge l

•Jun 21, 2018

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

автор: Parul

•Sep 17, 2017

excellent content.

автор: Songly H

•Nov 23, 2017

Great course, easy-to-understand teaching approaches!

автор: Olivia Z

•Jul 05, 2018

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

автор: GAYATHRI S

•Jan 02, 2018

It was great!

автор: Akshay H

•May 05, 2017

Best Course to understand Linear Regression.Thank you team Rice University for simple yet effective course on Linear Regression.Do enroll for this course if you want to understand linear regression thoroughly.

автор: Noro B

•Jul 22, 2017

Great source to learn regression with excel. Hard to find elsewhere !

автор: Lluís M

•Dec 09, 2017

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: Ponciano R

•May 21, 2018

This is a fantastic course and the teacher is excellent!

автор: Gregorio A A P

•Aug 26, 2017

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

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