Informações sobre o curso
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373 classificações
58 avaliações
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...
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Clock

Approx. 12 hours to complete

Sugerido: 4 weeks of study...
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English

Legendas: English...

Habilidades que você terá

Log–Log PlotInteraction (Statistics)Linear RegressionRegression Analysis
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Approx. 12 hours to complete

Sugerido: 4 weeks of study...
Comment Dots

English

Legendas: English...

Programa - O que você aprenderá com este curso

Week
1
Clock
5 horas para concluir

Regression Analysis: An Introduction

...
Reading
7 vídeos (Total de 65 min), 13 leituras, 7 testes
Video7 videos
Introducing Linear Regression: Building a Model8min
Introducing Linear Regression: Estimating the Model10min
Introducing Linear Regression: Estimating the Model12min
Introducing Linear Regression: Predictions using the Model9min
Errors, Residuals and R-square14min
Normality Assumption on the Errors7min
Reading13 leituras
Course FAQs10min
Pre-Course Survey10min
Toy Sales.xlsx10min
Slides, Lesson 110min
Toy Sales.xlsx10min
Slides, Lesson 210min
Toy Sales.xlsx10min
Slides, Lesson 310min
Toy Sales.xlsx10min
Slides, Lesson 410min
Toy Sales2.xlsx10min
Slides, Lesson 510min
Slides, Lesson 610min
Quiz7 exercícios práticos
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Regression Analysis: An Introductionmin
Week
2
Clock
5 horas para concluir

Regression Analysis: Hypothesis Testing and Goodness of Fit

...
Reading
6 vídeos (Total de 74 min), 15 leituras, 7 testes
Video6 videos
Hypothesis Testing in a Linear Regression: using 'p-values'7min
Hypothesis Testing in a Linear Regression: Confidence Intervals9min
A Regression Application Using Housing Data15min
'Goodness of Fit' measures: R-square and Adjusted R-square11min
Categorical Variables in a Regression: Dummy Variables18min
Reading15 leituras
Toy Sales.xlsx10min
Toy Sales (with regression).xlsx10min
Toy Sales (with regression, t-statistic).xlsx10min
Toy Sales (with regression, t-cutoff)10min
Slides, Lesson 110min
Toy Sales.xlsx10min
Slides, Lesson 210min
Toy Sales.xlsx10min
Slides, Lesson 310min
Home Prices.xlsx10min
Slides, Lesson 410min
Home Prices.xlsx10min
Slides, Lesson 510min
deliveries1.xlsx10min
Slides, Lesson 610min
Quiz7 exercícios práticos
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Regression Analysis: Hypothesis Testing and Goodness of Fitmin
Week
3
Clock
4 horas para concluir

Regression Analysis: Dummy Variables, Multicollinearity

...
Reading
6 vídeos (Total de 62 min), 12 leituras, 7 testes
Video6 videos
Dummy Variable Regression: Interpretation of Coefficients6min
Dummy Variable Regression: Estimation, Interpretation of p-values17min
A Regression Application Using Refrigerator data12min
A Regression Application Using Refrigerator data (continued...)7min
Multicollinearity in Regression Models: What it is and How to Deal with it10min
Reading12 leituras
deliveries2.xlsx10min
Slides, Lesson 110min
Slides, Lesson 210min
deliveries2.xlsx10min
deliveries2 (for prediction).xlsx10min
Slides, Lesson 310min
Refrigerators.xlsx10min
Slides, Lesson 410min
Cars.xlsx10min
Slides, Lesson 510min
Cars.xlsx10min
Slides, Lesson 610min
Quiz7 exercícios práticos
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Regression Analysis: Model Application and Multicollinearity20min
Week
4
Clock
4 horas para concluir

Regression Analysis: Various Extensions

...
Reading
7 vídeos (Total de 63 min), 11 leituras, 7 testes
Video7 videos
Building Confidence Bounds for Prediction Using a Regression Model9min
Interaction Effects in a Regression: An Introduction6min
Interaction Effects in a Regression: An Application8min
Transformation of Variables in a Regression: Improving Linearity7min
The Log-Log and the Semi-Log Regression Models17min
Course 4 Recap1min
Reading11 leituras
Height and Weight.xlsx10min
Slides, Lesson 110min
Height and Weight.xlsx10min
Slides, Lesson 210min
Slides, Lesson 310min
Height and Weight.xlsx10min
Slides, Lesson 410min
Slides, Lesson 510min
Cocoa.xlsx10min
Slides, Lesson 610min
End-of-Course Survey10min
Quiz7 exercícios práticos
Practice Quiz6min
Practice Quiz4min
Practice Quiz4min
Practice Quiz4min
Practice Quiz6min
Practice Quiz6min
Regression Analysis: Various Extensions22min
4.7
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50%

comecei uma nova carreira após concluir estes cursos
Briefcase

83%

consegui um benefício significativo de carreira com este curso
Money

25%

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Melhores avaliações

por WBDec 21st 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.

por MWMay 1st 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.

Instrutores

Sharad Borle

Associate Professor of Management
Jones Graduate School of Business

Sobre Rice University

Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy....

Sobre o Programa de cursos integrados Business Statistics and Analysis

The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques. You’ll master essential spreadsheet functions, build descriptive business data measures, and develop your aptitude for data modeling. You’ll also explore basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions. The Specialization culminates with a Capstone Project in which you’ll apply the skills and knowledge you’ve gained to an actual business problem. To successfully complete all course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later. To see an overview video for this Specialization, click here!...
Business Statistics and Analysis

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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