Quantitative Applications in the Social Sciences Ser.: Confidence Intervals by Michael Smithson (2002, Trade Paperback)

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About this product

Product Identifiers

PublisherSAGE Publications, Incorporated
ISBN-10076192499X
ISBN-139780761924999
eBay Product ID (ePID)27038426338

Product Key Features

Number of Pages104 Pages
LanguageEnglish
Publication NameConfidence Intervals
SubjectMethodology, Research, Statistics
Publication Year2002
TypeTextbook
AuthorMichael Smithson
Subject AreaSocial Science
SeriesQuantitative Applications in the Social Sciences Ser.
FormatTrade Paperback

Dimensions

Item Height0.2 in
Item Weight5 Oz
Item Length8.3 in
Item Width5.5 in

Additional Product Features

Intended AudienceCollege Audience
LCCN2002-009707
Dewey Edition21
Series Volume Number140
IllustratedYes
Dewey Decimal519.5/38
Table Of ContentCh 1 Introduction and OverviewCh 2 Confidence Statements and Interval Estimates Why Confidence Intervals?Ch 3 Central Confidence Intervals Central and Standardizable versus Noncentral Distributions Confidence Intervals Using the Central t and Normal Distributions Confidence Intervals Using the Central Chi-Square and F Distributions Transformation PrincipleCh 4 Noncentral Confidence Intervals for Standardized Effect Sizes Noncentral Distributions Computing Noncentral Confidence IntervalsCh 5 Applications in Anova and Regression Fixed-Effects ANOVA Random-Effects ANOVA A Priori and Post-Hoc Contrasts Regression: Multiple, Partial, and Semi-Partial Correlations Effect-Size Statistics for MANOVA and Setwise Regression Confidence Interval for a Regression Coefficient Goodness of Fit Indices in Structural Equations ModelsCh 6 Applications in Categorical Data Analysis Odds Ratio, Difference between Proportions and Relative Risk Chi-Square Confidence Intervals for One Variable Two-Way Contingency Tables Effects in Log-Linear and Logistic Regression ModelsCh 7 Significance Tests and Power Analysis Significance Tests and Model Comparison Power and Precision Designing Studies Using Power Analysis and Confidence Intervals Confidence Intervals for PowerConcluding RemarksReferencesAbout the Author
SynopsisUsing lots of easy to understand examples from different disciplines, Michael J Smithson introduces the basis of the confidence interval framework and provides the criteria for 'best' confidence intervals, along with the trade-offs between confidence and precision. Confidence Intervals covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter confidence intervals on distributions whose shape changes with the value of the parameter being estimated the relationship between confidence interval and significance testing frameworks, particularly regarding power., Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision. Next, using a reader-friendly style with lots of worked out examples from various disciplines, he covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated; and, the relationship between confidence interval and significance testing frameworks, particularly regarding power., Using lots of easy to understand examples from different disciplines, the author introduces the basis of the confidence interval framework and provides the criteria for 'best confidence intervals, along with the trade-offs between confidence and precision. The book covers such pertinent topics as: - the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter - confidence intervals on distributions whose shape changes with the value of the parameter being estimated - the relationship between confidence interval and significance testing frameworks, particularly regarding power.
LC Classification NumberHA31.2.S59 2003
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