Detalles MARC
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13922nam a22005413i 4500 |
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EBC4605618 |
| 003 - CONTROL NUMBER IDENTIFIER |
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MiAaPQ |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20221014180512.0 |
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| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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211129s2016 nyua go ||0|0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781119121053 |
| Qualifying information |
(electronic bk.) |
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| Canceled/invalid ISBN |
9781119121077 |
| 035 ## - |
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| System control number |
(MiAaPQ)EBC4605618 |
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| System control number |
(Au-PeEL)EBL4605618 |
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| System control number |
(CaPaEBR)ebr11238649 |
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| System control number |
(CaONFJC)MIL941785 |
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| System control number |
(OCoLC)954284941 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
MiAaPQ |
| Language of cataloging |
eng |
| Description conventions |
rda |
| -- |
pn |
| Transcribing agency |
MiAaPQ |
| Modifying agency |
MiAaPQ |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA276.4 |
| Item number |
.A236 2017 |
| 082 0# - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
300.727 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Abbott, Martin Lee. |
| Relator term |
author |
| 245 10 - TITLE STATEMENT |
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| Title |
Using Statistics in the Social and Health Sciences with SPSS and Excel / |
| Statement of responsibility, etc. |
Martin Lee Abbott. |
| 264 #1 - |
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| Place of production, publication, distribution, manufacture |
Newark : |
| Name of producer, publisher, distributor, manufacturer |
John Wiley & Sons, Incorporated, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2016. |
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| Date of production, publication, distribution, manufacture, or copyright notice |
©2017. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
1 online resource (585 pages) |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Content type code |
txt |
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rdacontent |
| 337 ## - MEDIA TYPE |
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computer |
| Media type code |
c |
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rdamedia |
| 338 ## - CARRIER TYPE |
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| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 505 0# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Cover -- Title Page -- Copyright -- Dedication -- Contents -- Preface -- Acknowledgments -- Chapter 1 Introduction -- Big Data Analysis -- Visual Data Analysis -- Importance of Statistics for the Social and Health Sciences and Medicine -- Historical Notes: Early Use of Statistics -- Approach of the Book -- Cases from Current Research -- Research Design -- Focus on Interpretation -- Coverage of Statistical Procedures -- Chapter 2 Descriptive Statistics: Central Tendency -- What is the Whole Truth? Research Applications (Spuriousness) -- Descriptive and Inferential Statistics -- The Nature of Data: Scales of Measurement -- Nominal Data -- Ordinal Data -- Interval Data -- Ratio Data -- Choosing the Correct Statistical Procedure for the Nature of Research Data -- Descriptive Statistics: Central Tendency -- Mean -- Median -- Mode -- Central Tendency and Levels of Data -- Using SPSS® and Excel to Understand Central Tendency -- SPSS® -- Excel -- Distributions -- Describing the Normal Distribution: Numerical Methods -- Central Tendency -- Skewness -- Kurtosis -- Descriptive Statistics: Using Graphical Methods -- Frequency Distributions -- Column Charts" in Excel -- Bar Charts" and "Histograms -- Bar Charts and Histograms in SPSS® -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Chapter 3 Descriptive Statistics: Variability -- Range -- Percentile -- Scores Based on Percentiles -- Using SPSS® and Excel to Identify Percentiles -- SPSS® Procedures -- Excel Procedures -- Standard Deviation and Variance -- Calculating the Variance and Standard Deviation -- The Deviation Method -- The Average Deviation -- The Computation Method -- The Sum of Squares -- Population SD and Inferential SD -- Obtaining SD from Excel and SPSS® -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions. |
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| Formatted contents note |
Chapter 4 The Normal Distribution -- The Nature of the Normal Curve -- The Standard Normal Score: Z Score -- The Z Score Table of Values -- Navigating the Z Score Distribution -- Calculating Percentiles -- Creating Rules for Locating Z Scores -- Calculating Z Scores -- Working with Raw Score Distributions -- Using SPSS® to Create Z Scores and Percentiles -- Creating Z Scores -- Creating Percentiles in SPSS® -- Using Excel to Create Z Scores -- STANDARDIZE Function -- Using Excel and SPSS® for Distribution Descriptions -- NORM.S.DIST Function -- NORM.DIST Function -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Chapter 5 Probability And the Z Distribution -- The Nature of Probability -- Elements of Probability -- Empirical Probability -- Combining Probabilities -- Combining Probabilities: Addition Rule -- Combining Probabilities: Multiplication Rule -- Combinations and Permutations -- Combination -- Permutation -- Conditional Probability: Using Bayes' Theorem -- Z Score Distribution and Probability -- Transforming a Raw Score to a Z Score: Statistical Testing -- Transforming a Z Score to a Raw Score: Estimation -- Transforming Cumulative Proportions to z Scores -- Deriving Sample Scores from Cumulative Percentages -- Using SPSS® and Excel to Transform Scores -- Using the Attributes of the Normal Curve to Calculate Probability -- Calculating "Areas" of the Standard Normal Distribution -- Inclusion Area Example -- Exclusion Area Example -- Exact" Probability -- Estimating "Exact" Probabilities -- From Sample Values to Sample Distributions -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Chapter 6 Research Design and Inferential Statistics -- Research Design -- Theory -- Hypothesis -- Types of Research Designs -- Experiment -- Randomization -- Control and Treatment Groups. |
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| Formatted contents note |
Variables -- Quasi-Experimental Design -- Non-Experimental or Post Facto Research Designs -- The Nature of Research Design -- Research Design Varieties -- Sampling -- Inferential Statistics -- One Sample from Many Possible Samples -- Central Limit Theorem and Sampling Distributions -- The Sampling Distribution and Research -- Populations and Samples -- The Standard Error of the Mean -- Transforming" the Sample Mean to the Sampling Distribution -- Example -- Findings -- Discussion -- Z Test -- The Hypothesis Test -- Statistical Significance -- Practical Significance: Effect Size -- Z Test Elements -- Using SPSS® and Excel for the Z Test -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Chapter 7 The T Test for Single Samples -- Introduction -- Z Versus T: Making Accommodations -- Research Design -- Experiment -- Post Facto: Comparative Design -- Parameter Estimation -- Estimating the Population SD -- New Symbol Sx: The Estimated SD of the Population -- Biased versus Unbiased Estimates -- New Symbol Sm: The Estimated SD of the Sampling Distribution of Means (or Simply, "Standard Error of the Mean") -- The T Test -- Degrees of Freedom -- The T Test: A Research Example -- Sample and Population Means (M- ) -- The Estimated Population SD (Sx) and Estimated Standard Error of the Mean (Sm) -- Calculating the T Ratio Value -- Interpreting the Results of the T Test for a Single Mean -- The T Distribution -- Using df with the T Distribution -- The Hypothesis Test for the Single Sample T Test -- Type I and Type II Errors -- Type I (Alpha) Errors ( ) -- Type II (Beta) Errors ( ) -- Areas of Comparison Distributions -- Effect Size -- Effect Size for the Single Sample T Test -- Another Measurement of the (Cohen's d) Effect Size -- Power, Effect Size, and Beta -- One- and Two-Tailed Tests -- Two-Tailed Tests. |
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| Formatted contents note |
One-Tailed Tests -- Choosing a One- or Two-Tailed Test -- A Note about Power -- Point and Interval Estimates -- Calculating the Interval Estimate of the Population Mean -- The Value of Confidence Intervals -- Using SPSS® and Excel with the Single Sample T Test -- SPSS® and the Single Sample T test -- Excel and the Single Sample T test -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Chapter 8 Independent Sample T Test -- A Lot of "Ts -- Research Design -- Experimental Designs and the Independent T Test -- Dependent Sample Designs -- Between and Within Research Designs -- Using Different T Tests -- Pre-test or No Pre-test -- Example of Experiment -- Post Facto Designs -- Independent T Test: The Procedure -- Creating the Sampling Distribution of Differences -- The Nature of the Sampling Distribution of Differences -- The Mean and Standard Deviation of the Sampling Distribution of Differences -- Calculating the Estimated Standard Error of Difference with Equal Sample Size -- The Degrees of Freedom for the Independent T Test -- Using Unequal Sample Sizes -- Derivation of the Formula for Unequal Sample Sizes -- The Independent T Ratio -- Independent T Test Example -- The Setting -- The Research Data -- Hypothesis Test Elements for the Example -- The Null Hypothesis -- The Alternative Hypothesis -- The Critical Value of Comparison -- The Calculated T Ratio -- Statistical Decision -- Interpretation -- Research Design of the Example -- Before-After Convention with the Independent T Test -- Confidence Intervals for the Independent T Test -- Effect Size -- Cohen's d Method -- The Eta Squared Method -- The Assumptions for the Independent T Test -- Assumptions 1 and 2: Independence and Interval Level -- Assumption 3: Normal Distribution of Sample Groups -- Assumption 4: Equal Variance. |
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| Formatted contents note |
SPSS® Explore for Checking the Normal Distribution Assumption -- Excel Procedures for Checking the Equal Variance Assumption -- F Distribution -- Use "Right" Side Critical Values -- What Outcome Meets the Assumption for Equality of Variances? -- SPSS® Procedure for Checking the Equal Variance Assumption -- The Homogeneity of Variance Assumption for the Independent T Test -- A Rule of Thumb -- Using SPSS® and Excel with the Independent T Test -- SPSS® Procedures for the Independent T Test -- Excel Procedures for the Independent T Test -- Effect Size for the Independent T Test Example -- Parting Comments -- Nonparametric Statistics: The Mann-Whitney U Test -- Terms and Concepts -- Data Lab and Examples (with Solutions) -- Data Lab: Solutions -- Graphics in the Data Summary -- Chapter 9 Analysis of Variance -- A Hypothetical Example of ANOVA -- The Nature of ANOVA -- The Components of Variance -- The Process of ANOVA -- Calculating ANOVA -- Calculating the Variance: Using the Sum of Squares (SS) -- Calculating Components of Variance Using SS -- Creating a Data Table -- Using Mean Squares (MS) -- Degrees of Freedom in ANOVA -- Calculating Mean Squares (MS) -- The F Ratio -- The F Distribution -- Effect Size -- Post Hoc Analyses -- Varieties" of Post Hoc Analyses -- The Post Hoc Analysis Process -- Tukey's HSD (Range) Test Calculation -- Mean Comparison Table -- Compare Mean Difference Values from HSD -- Post Hoc Summary -- Assumptions of ANOVA -- Additional Considerations with ANOVA -- The Hypothesis Test: Interpreting ANOVA Results -- Are the Assumptions Met? -- Is Population Normally Distributed? -- Are the Variances Equal? -- Are the Samples Independently Chosen? -- Does the Dependent Variable Consist of Interval Data? -- Manual Calculations -- Post Hoc Analysis -- Using SPSS® and Excel with One-Way ANOVA -- SPSS® Procedures with One-Way ANOVA. |
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| Formatted contents note |
General Linear Model (GLM) Approach to Analyzing ANOVA. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Provides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications This book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field. The book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material. Using Statistics in the Social and Health Sciences with SPSS® and Excel® includes: Use of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings Inclusion of a data lab section in each chapter that provides relevant, clear examples Introduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs Emphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data. |
| 588 ## - |
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| Source of description note |
Description based on publisher supplied metadata and other sources. |
| 590 ## - LOCAL NOTE (RLIN) |
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| Local note |
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. |
| 630 #0 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
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| 9 (RLIN) |
173531 |
| Uniform title |
SPSS Computer file |
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| 9 (RLIN) |
136099 |
| Uniform title |
Microsoft Excel (Computer file) |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Mathematical statistics |
| 9 (RLIN) |
132755 |
| General subdivision |
Data processing. |
| 655 #4 - |
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| Genre/form data or focus term |
Electronic books. |
| 776 08 - |
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| Relationship information |
Print version: |
| Main entry heading |
Abbott, Martin Lee |
| Title |
Using Statistics in the Social and Health Sciences with SPSS and Excel |
| Place, publisher, and date of publication |
Newark : John Wiley & Sons, Incorporated,c2016 |
| International Standard Book Number |
9781119121077 |
| 797 2# - |
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| Corporate name or jurisdiction name as entry element |
ProQuest (Firm) |
| 856 ## - |
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| Uniform Resource Identifier |
https://login.ezproxy.pucpr.edu/login?url=https://ebookcentral.proquest.com/lib/pucpr-ebooks/detail.action?docID=4605618 |
| Link text |
Acceso Remoto |
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| Uniform Resource Identifier |
https://ebookcentral.proquest.com/lib/pucpr-ebooks/detail.action?docID=4605618 |
| Link text |
Acceso en el Campus PUCPR |
| 942 ## - |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Libro electrónico |