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[ 洋図書 ] Statistics for people who (think they) hate statistics /

Neil J. Salkind. -- SAGE, -- c2014. -- 5th ed.

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ISBN [1452277710] (pbk.)
ISBN13桁 9781452277714 (pbk.)
テキストの言語 英語                  
分類：NDC10版 417
個人著者標目 Salkind, Neil J.
本タイトル Statistics for people who (think they) hate statistics /
著者名 Neil J. Salkind.
その他のタイトル Statistics for people who think they hate statistics
版表示 5th ed.
出版地・頒布地 Thousand Oaks, Calif. :
出版者・頒布者名 SAGE,
出版年・頒布年 c2014.
数量 xxvii, 483 p. :
他の形態的事項 ill. ;
大きさ 26 cm.
書誌注記 Includes bibliographical references and index.
内容注記 Machine generated contents note: pt. I Yippee! I'm in Statistics -- 1.Statistics or Sadistics? It's Up to You -- Why Statistics? -- A 5-Minute History of Statistics -- Statistics: What It Is (and Isn't) -- What Are Descriptive Statistics? -- What Are Inferential Statistics? -- In Other Words -- What Am I Doing in a Statistics Class? -- Ten Ways to Use This Book (and Learn Statistics at the Same Time!) -- About Those Icons -- Key to Difficulty Index -- Glossary -- Real-World Stats -- Summary -- Time to Practice -- pt. II Sigma -- Freud and Descriptive Statistics -- 2.Means to an End: Computing and Understanding Averages -- Computing the Mean -- Things to Remember -- Computing a Weighted Mean -- Computing the Median -- Things to Remember -- Computing the Mode -- Apple Pie a la Bimodal -- When to Use What -- Using the Computer and Computing Descriptive Statistics -- The SPSS Output -- Real-World Stats -- Summary -- Time to Practice -- 3.Vive la Difference: Understanding Variability -- Why Understanding Variability Is Important -- Computing the Range -- Computing the Standard Deviation -- Why n -- l? What's Wrong With Just n? -- What's the Big Deal? -- Things to Remember -- Computing the Variance -- The Standard Deviation Versus the Variance -- Using the Computer to Compute Measures of Variability -- The SPSS Output -- Real-World Stats -- Summary -- Time to Practice -- 4.A Picture Really Is Worth a Thousand Words -- Why Illustrate Data? -- Ten Ways to a Great Figure (Eat Less and Exercise More?) -- First Things First: Creating a Frequency Distribution -- The Classiest of Intervals -- The Plot Thickens: Creating a Histogram -- The Tallyho Method -- The Next Step: A Frequency.Polygon -- Cumulating Frequencies -- Fat and Skinny Frequency Distributions -- Average Value -- Variability -- Skewness -- Kurtosis -- Other Cool Ways to Chart Data -- Column Charts -- Bar Charts -- Line Charts -- Pie Charts -- Using the Computer (SPSS, That Is) to Illustrate Data -- Creating a Histogram -- Creating a Bar Graph -- Creating a Line Graph -- Creating a Pie Chart -- Real-World Stats -- Summary -- Time to Practice -- 5.Ice Cream and Crime: Computing Ccirrelation Coefficients -- What Are Correlations All About? -- Types of Correlation Coefficients: Flavor 1 and Flavor 2 -- Things to Remember -- Computing a Simple Correlation Coefficient -- A Visual Picture of a Correlation: The Scatterplot -- Bunches of Correlations: The Correlation Matrix -- Understanding What the Correlation Coefficient Means -- Using-Your-Thumb Rule -- A Determined Effort: Squaring the Correlation Coefficient -- As More Ice Cream Is Eaten . . . the Crime Rate Goes Up (or Association vs. Causality) -- Other Cool Correlations -- Using the Computer to Compute a Correlation Coefficient -- The SPSS Output -- Creating a Scatterplot (or Scattergram or Whatever) -- Real-World Stats -- Summary -- Time to Practice -- 6.Just the Truth: An Introduction to Understanding Reliability and Validity -- An Introduction to Reliability and Validity -- What's Up With This Measurement Stuff? -- All About Measurement Scales -- A Rose by Any Other Name: The Nominal Level of Measurement -- Any Order Is Fine With Me: The Ordinal Level of Measurement -- 1 + 1 = 2: The Interval Level of Measurement -- Can Anyone Have Nothing of Anything? The Ratio Level of Measurement -- In Sum -- Reliability: Doing It Again Until You Get It Right -- Test Scores: Truth or Dare? -- Observed Score = True Score + Error Score -- Different Types of Reliability -- Using the Computer to Calculate Cronbach's Alpha -- What the SPSS Output Means -- How Big Is Big? Finally: Interpreting Reliability Coefficients -- And If You Can't Establish Reliability Then What? -- Just One More Thing -- Validity: Whoa! What Is the Truth? -- Different Types of Validity -- A Last Friendly Word -- Validity and Reliability: Really Close Cousins -- Real-World Stats -- Summary -- Time to Practice -- pt. III Taking Chances for Fun and Profit -- 7.Hypotheticals and You: Testing Your Questions -- So You Want to Be a Scientist -- Samples and Populations -- The Null Hypothesis -- The Purposes of the Null Hypothesis -- The Research Hypothesis -- The Nondirectional Research Hypothesis -- The Directional Research Hypothesis -- Some Differences Between the Null Hypothesis and the Research Hypothesis -- What Makes a Good Hypothesis? -- Real-World Stats -- Summary -- Time to Practice -- 8.Are Your Curves Normal? Probability and Why It Counts -- Why Probability? -- The Normal Curve (a.k.a. the Bell-Shaped Curve) -- Hey, That's Not Normal! -- More Normal Curve 101 -- Our Favorite Standard Score: The z Score -- What z Scores Represent -- What z Scores Really Represent -- Hypothesis Testing and z Scores: The First Step -- Using the Computer to Compute z Scores -- Real-World Stats -- Summary -- Time to Practice -- pt. IV Significantly Different: Using Inferential Statistics -- 9.Significantly Significant: What It Means for You and Me -- The Concept of Significance -- If Only We Were Perfect -- The World's Most Importantlable (for This Semester Only) -- More About Table 9.1 -- Back to Type I Errors -- Significance Versus Meaningfulness -- An Introduction to Inferential Statistics -- How Inference Works -- How to Select What Test to Use -- Here's How to Use the Chart -- An Introduction to Tests of Significance -- How a Test of Significance Works: The Plan -- Here's the Picture That's Worth a Thousand Words -- Be Even More Confident -- Real-World Stats -- Sumthary -- Time to Practice -- 10.Only the Lonely: The One-Sample Z-Test -- Introduction to the One-Sample z-Test -- The Path to Wisdom and Knowledge -- Computing the Test Statistic -- So How Do I Interpret z = 2.38, p < .05? -- Real-World Stats -- Summary -- Time to Practice -- 11.t(ea) for Two: Tests Between the Means of Different Groups -- Introduction to the t-Test for Independent Samples -- The Path to Wisdom and Knowledge -- Computing the Test Statistic -- So How Do I Interpret t(58) = -- .14, p > .05? -- Special Effects: Are Those Differences for Real? -- Computing and Understanding the Effect Size -- A Very Cool Effect Size Calculator -- Using the Computer to Perform a t-Test -- What the SPSS Output Means -- Real-World Stats -- Summary -- Time to Practice -- 12.t(ea) for Two (Again): Tests Between the Means of Related Groups -- Introduction to the t-Test for Dependent Samples -- The Path to Wisdom and Knowledge -- Computing the Test Statistic -- So How Do I Interpret t(24) = 2.45, p < .05? -- Using the Computer to Perform a t-Test -- What the SPSS Output Means -- Real-World Stats -- Summary -- Time to Practice -- 13.Two Groups Too Many? Try Analysis of Variince -- Introduction to Analysis of Varianbe -- The Path to Wisdom and Knowledge' -- Different Flavors of ANOVA -- Computing the F-Test Statistic -- So How Do I Interpret F(2, 27) = 8.80, p < .05? -- Using the Computer to Compute the F Ratio -- What the SPSS Output Means -- Real-World Stats -- Summary -- Time to Practice -- 14.Two Too Many Factors: Factorial Analysis of Variance -- A Brief Introduction -- Introduction to Factorial Analysis of Variance -- The Path to Wisdom and Knowledge -- A New FlaVOr of·ANOVA -- The Main Event: Main Effects in Factorial ANOVA -- Even More Interesting: Interaction Effects -- Things to Remember -- Using the Computer to Compute the F Ratio -- What the SPSS Output Means -- Real-World Stats -- Summary -- Time to Practice -- 15.Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient -- Introduction to Testing the Correlation Coefficient -- The Path to Wisdom and Knowledge -- Computing the Test Statistic -- So How Do I Interpret r(28) .437, p < .05? -- Causes and Associations (Again!) -- Significance Versus Meaningfulness (Again, Again!) -- Using the Computer to Compute a Correlation Coefficient (Again) -- What the SPSS Output Means -- Real-World Stats -- Summary -- Time to Practice -- 16.Predicting Who'll Win the Super Bowl: Using Linear Regression -- What Is Prediction All About? -- The Logic of Prediction -- Drawing the World's Best Line (for Your Data) -- How Good Is Our Prediction? -- Using the Computer to Compute the Regression Line -- What the SPSS Output Means -- The More Predictors the Better? Maybe -- The Big Rule(s) When It Comes to Using Multiple Predictor Variables -- Real-World Stats -- Summary -- Time to Practice -- 17.What to Do When You're Not Normal: Chi-Square and Some Other Nonparametric Tests -- Introduction to Nonparametric Statistics -- Introduction to One-Sample Chi-Square -- Computing the Chi-Square Test Statistic -- So How Do I Interpiet x2(2) = 20.6, p < .05? -- Using the Computer to Perform a Chi-Square Test -- What the SPSS Output Means -- Other Nonparametric Tests You Should Know About -- Real-World Stats -- Summary -- Time to Practice -- 18.Some Other (Important) Statistical Procedures You Should Know About -- Multivariate Analysis of Variance -- Repeated Measures Analysis of Variance -- Analysis of Covariance -- Multiple Regression -- Meta-analysis -- Discriminant Analysis -- Factor Analysis -- Path Analysis -- Structural Equation Modeling -- Summary -- 19.A Statistical Software Sampler -- Selecting the Perfect Statistics Software -- What's Out There -- First, the Free Stuff -- Time to Pay -- Summary -- pt. V Ten Things You'll Want to Know and Remember -- 20.The 10 (or More) Best Internet Sites for Statistics Stuff -- Tons and Tons of Resources -- Who's Who and What's Happened? -- It's All Here -- HyperStat -- Data? You Want Data? -- Fun -- Really Fun -- More and More and More and More Resources -- How About Studying Statistics in Stockholm? -- Online Statistical Teaching Materials -- Around the World -- And Finally -- 21.The 10 Commandments of Data Collection.
一般件名 Statistics.
資料情報1 『Statistics for people who (think they) hate statistics /』5th ed.　Neil J. Salkind.　SAGE,　c2014. （所蔵館：中央　 請求記号：F/417.0/S16/S　 資料コード：7104018386）
URL https://catalog.library.metro.tokyo.lg.jp/winj/opac/switch-detail.do?lang=ja&bibid=1352010743

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