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Regression with Dummy Variables: 93 ... by Hardy, Melissa A Paperback / softback
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A book that has been read and does not look new, but is in excellent condition. No obvious damage to the book cover, with the dust jacket (if applicable) included for hard covers. No missing or damaged pages, no creases or tears, no underlining or highlighting of text, and no writing in the margins. Some identifying marks on the inside cover, but this is minimal. Very little wear and tear. See the seller’s listing for full details and description of any imperfections.
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eBay item number:305303159844
Item specifics
- Condition
- ISBN
- 0803951280
- EAN
- 9780803951280
- Date of Publication
- 1993-04-23
- Release Title
- Regression with Dummy Variables: 93 (Quantitative Applications...
- Artist
- Hardy, Melissa A
- Brand
- N/A
- Colour
- N/A
- Book Title
- Regression with Dummy Variables: 93 (Quantitative Applications...
About this product
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
0803951280
ISBN-13
9780803951280
eBay Product ID (ePID)
309308
Product Key Features
Number of Pages
96 Pages
Publication Name
Regression with Dummy Variables
Language
English
Publication Year
1993
Subject
Probability & Statistics / Regression Analysis, Research, Statistics
Type
Textbook
Subject Area
Mathematics, Social Science
Series
Quantitative Applications in the Social Sciences Ser.
Format
Trade Paperback
Dimensions
Item Height
0.2 in
Item Weight
5 Oz
Item Length
8.5 in
Item Width
5.5 in
Additional Product Features
Intended Audience
Scholarly & Professional
Series Volume Number
93
Volume Number
Vol. 93
Illustrated
Yes
Table Of Content
IntroductionCreating Dummy VariablesUsing Dummy Variables as RegressorsAssessing Group Differences in EffectsAlternative Coding Schemes for Dummy VariablesSpecial Topics in the Use of Dummy VariablesConclusions
Synopsis
It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behavior, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression., It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behaviour, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity and estimating a piecewise linear regression., Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.
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- 07 Dec, 2020
Great book for a great value.
Verified purchase: YesCondition: Pre-ownedSold by: goodwillbks
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