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Multiple Regression: A Practical Introduction by Roberts
US $95.99
ApproximatelyS$ 122.88
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A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages.
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eBay item number:365638571182
Item specifics
- Condition
- Good
- Seller Notes
- “Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
- Book Title
- Multiple Regression: A Practical Introduction
- Topic
- Statistics
- Narrative Type
- Statistics
- Genre
- N/A
- Intended Audience
- N/A
- ISBN
- 9781544339702
About this product
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
1544339704
ISBN-13
9781544339702
eBay Product ID (ePID)
7050409805
Product Key Features
Number of Pages
280 Pages
Publication Name
Multiple Regression : a Practical Introduction
Language
English
Publication Year
2020
Subject
Sociology / General, Probability & Statistics / General, Statistics, Criminology
Type
Textbook
Subject Area
Mathematics, Social Science
Format
Trade Paperback / Trade Paperback
Dimensions
Item Weight
18 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
Intended Audience
College Audience
LCCN
2020-948981
Reviews
This book gives students the practical knowledge and foundation of regression analysis. It is refreshing that the book includes twochapters the extend past linear regression to other types of analysis., This book gives students the practical knowledge and foundation of regression analysis. It is refreshing that the book includes two chapters the extend past linear regression to other types of analysis. -- Margaret Ralston
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
300.1519536
Table Of Content
Chapter 1 IntroductionChapter 2 Fundamentals of Multiple RegressionChapter 3 Categorical Independent Variables in Multiple Regression: Dummy VariablesChapter 4 Multiple Regression with InteractionChapter 5 Logged Variables in Multiple RegressionChapter 6 Nonlinear Relationships in Multiple RegressionChapter 7 Categorical Dependent Variables: Logistic RegressionChapter 8 Count Dependent Variables: Poisson RegressionChapter 9 A Brief Tour of Some Related Methods
Synopsis
Multiple Regression: A Practical Introduction is a text for an advanced undergraduate or beginning graduate course in statistics for social science and related fields. Drawing on decades of teaching this material, the authors present the ideas in an approachable and nontechnical manner, with no expectation that readers have more than a standard introductory statistics course as background. The book includes many interesting example analyses and interpretations, along with exercises., Including many interesting example analyses and interpretations, along with exercises, this text offers a practical introduction to multiple regression. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered. SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book are available on an accompanying website, along with solutions to the exercises (on the instructor site)., Multiple Regression: A Practical Introduction is a text for an advanced undergraduate or beginning graduate course in statistics for social science and related fields. Also, students preparing for more advanced courses can self-study the text to refresh and solidify their statistical background. Drawing on decades of teaching this material, the authors present the ideas in an approachable and nontechnical manner, with no expectation that readers have more than a standard introductory statistics course as background. Multiple regression asks how a dependent variable is related to, or predicted by, a set of independent variables. The book includes many interesting example analyses and interpretations, along with exercises. Each dataset used for the examples and exercises is small enough for readers to easily grasp the entire dataset and its analysis with respect to the specific statistical techniques covered. A website for the book includes SPSS, Stata, SAS, and R code and commands for each type of analysis or recoding of variables in the book. Solutions to two of the end-of-chapter exercise types are also available for students to practice. The instructor side of the site contains editable PowerPoint slides, other solutions, and a test bank.
LC Classification Number
HA31.3
Item description from the seller
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