Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

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678 APPENDIX C | Solutions for Odd-Numbered Problems in the TextSource SS df MSBetween Treatments 32 5Use 24 1 24 F(1, 18) = 14.4School level 4 2 2 F(2, 18) = 1.2Interaction 4 2 2 F(2, 48) = 1.2Within Treatments 30 18 1.67Total 62 23For df = 1, 18 the critical value is 4.41 and fordf = 2, 18 it is 3.55. The main effect for Facebookuse is significant. For df = 2, 18 the critical value is3.55. The other main effect and the interaction arenot significant.b. Grades are significantly lower for Facebookusers. A difference exists for all three grade levelsbut appears to increase as the students get olderalthough there is no significant interaction.25. a.Source SS df MSBetween Treatments 270 3Self-Esteem 150 1 150 F(1, 20) = 34.88Audience 96 1 96 F(1, 20) = 22.33Interaction 24 1 24 F(1, 20) = 5.58Within Treatments 86 20 4.3Total 356 23With df = 1, 20 the critical value is 4.35 for all threetests. Both main effects and the interaction are significant.Overall, there are fewer errors for the high selfesteemparticipants and for those working alone. Theaudience condition has very little effect on the highself-esteem participants but a very large effect on thosewith low self-esteem.b. For the self-esteem main effect, η 2 = 150236 = 0.636,for the audience main effect, η 2 = 96182 = 0.527, andfor the interaction, η 2 = 24110 = 0.218.CHAPTER 15Correlation1. A positive correlation indicates that X and Y change inthe same direction: As X increases, Y also increases.A negative correlation indicates that X and Y tendto change in opposite directions: As X increases, Ydecreases.3. SP = 95. a. The scatter plot shows points widely scatteredaround a line sloping down to the right.b. The correlation is small and negative; around −0.4to −0.6.c. For these scores, SS X= 18, SS Y= 8, andSP = −7. The correlation is r = 2 712 = −0.583.7. a. The scatter plot shows four points forming asquare. There is no linear trend so the correlationis near zero.b. SS X= 9, SS Y= 25, and SP = 0. The correlation isr = 015 = 0.9. a. The scatter plot shows points scattered around aline sloping up to the right. The correlation shouldbe 0.4 to 0.6.b. SS X= 6, SS Y= 24, and SP = 5. The correlation isr = 512 = 0.42.11. a. For the children, SS = 32 and for the birthparents, SS = 14. SP = 15. The correlation isr = 0.709.b. For the children, SS = 32 and for the adoptiveparents SS = 16. SP = 3. The correlation isr = 0.133.c. The children’s behavior is strongly related to theirbirth parents and only weakly related to theiradoptive parents. The data suggest that the behavioris inherited rather than learned.13. a. For the men’s weights, SS = 18 and for theirincomes, SS = 11,076. SP = 330. The correlationis r = 0.739.b. With n = 8, df = 6 and the critical value is 0.707.The correlation is significant.15. a. r = 0.811b. r = 0.576c. r = 0.40417. a. r XY−Z= 0.320.655 = 0.489b. r XZ−Y= 2 0.020.571 = −0.03519. a. r S= +0.907b. With n = 11, the critical value is 0.618. The correlationis significant.21. a. r S= 0.732 using the special formula orr S= 0.727 using the Pearson formula onthe ranks.b. For n = 8, the critical value is 0.738 forα = .05. The correlation is not significant.23. a. Using the pain ratings as the X variable and codingmoney as 1 and plain paper as 0 for the Y variableproduces SS X= 144.44, SS Y= 4.5, and SP = −17.The point-biserial correlation is r = −0.667.b. r 2 = 0.445c. The formula produces r 2 = 0.443.
APPENDIX C | Solutions for Odd-Numbered Problems in the Text 679CHAPTER 16Introduction To Regression1. Figure C4Y7 Y 5 2X 2 1654Y 5 2X 1 8321X654321073. a. r = 0.25b. Ŷ = 0.5X + 65. The standard error of estimate is a measure of theaverage distance between the predicted Y points fromthe regression equation and the actual Y points inthe data.7. SS X= 16, SS Y= 134, SP = 32. With M X= 4 andM Y= 6, the regression equation is Ŷ = 2X − 2.9. SS regression= r 2 SS Y= 39.95 with df = 1. MS residual=10.05439.95= 2.51. F = 2.51 = 15.92. With df = 1, 4, theF-ratio is significant with Ŷ = .05.11. a. SS weight= 18,SS income= 21,609, SP = 330.Ŷ = 18.33X + 33b. r = −0.529 and r 2 = 0.280c. F = 2.33 with df = 1, 6. The regressionequation is not significant.13. a. Ŷ = 1.38X + 7.34b. r 2 = 0.743 or 74.3%c. F = 20.23 with df = 1, 7. The equation accountsfor a significant portion of the variance.15. a. The standard error of estimate is Ï 3616 = 1.50.b. The standard error of estimate isÏ 3664 = 0.75.17. a. df = 1, 18b. n = 25 pairs of scores19. a. F = 7.61.46 = 5.21. With df = 2, 17, the critical valueis 3.59. The equation does account for a significantportion of the variance.b. F = 7.63.54 = 2.15. With df = 2, 7, the equation isnot significant.21. a. SS crime= 230, SS prevention= 230, SS population= 8, and.SP for crime and prevention is 40, SP for crimeand population is 40, and SP for prevention andpopulation is 176, and. The regression equation isŶ = −0.8X 119X 2, where X 1is the amount spenton prevention and X 2is the population.b. R 2 = 0.953 or 93.5%23. Ŷ = 1.242X 1− 0.048X 2+ 0.565
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EDITION10Statistics for theBehavior
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Statistics for the Behavioral Scien
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CONTENTSCHAPTER 1 Introduction to S
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CONTENTSvii5.4 Using z-Scores to St
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CONTENTSixCHAPTER 10 The t Test for
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CONTENTSxiCHAPTER 15 Correlation 48
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PREFACEMany students in the behavio
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PREFACExv3. The former Chapter 19,
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PREFACExviiTo the StudentA primary
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ABOUT THE AUTHORSFREDERICK J GRAVET
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PREVIEWBefore we begin our discussi
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4 CHAPTER 1 | Introduction to Stati
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10 CHAPTER 1 | Introduction to Stat
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PREVIEWThere is some evidence that
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36 CHAPTER 2 | Frequency Distributi
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Central TendencyCHAPTER3Tools You W
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SECTION 3.1 | Overview 69DEFINITION
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SECTION 3.2 | The Mean 71research r
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SECTION 3.2 | The Mean 73the distri
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SECTION 3.2 | The Mean 75TABLE 3.1S
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SECTION 3.2 | The Mean 77Table 3.2
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SECTION 3.3 | The Median 793.3 The
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SECTION 3.3 | The Median 81To find
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SECTION 3.4 | The Mode 832. What is
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SECTION 3.4 | The Mode 85FIGURE 3.7
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SECTION 3.6 | Central Tendency and
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FOCUS ON PROBLEM SOLVING 95of centr
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PROBLEMS 976. A population of N = 1
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VariabilityCHAPTER4Tools You Will N
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SECTION 4.1 | Introduction to Varia
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SECTION 4.2 | Defining Standard Dev
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SECTION 4.5 | Sample Variance as an
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SECTION 4.6 | More about Variance a
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SUMMARY 1252. A population has a me
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FOCUS ON PROBLEM SOLVING 127VAR0000
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PROBLEMS 1299. For the following se
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z-Scores: Location of Scoresand Sta
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SECTION 5.1 | Introduction to z-Sco
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SECTION 5.2 | z-Scores and Location
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SECTION 5.2 | z-Scores and Location
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SECTION 5.3 | Other Relationships B
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SECTION 5.4 | Using z-Scores to Sta
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SECTION 5.4 | Using z-Scores to Sta
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SECTION 5.5 | Other Standardized Di
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SECTION 5.5 | Other Standardized Di
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SECTION 5.6 | Computing z-Scores fo
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SECTION 5.7 | Looking Ahead to Infe
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SUMMARY 153LEARNING CHECK1. In N =
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DEMONSTRATION 5.2 155sure that your
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PROBLEMS 15716. A distribution of e
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PREVIEWHow likely is it that you wi
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162 CHAPTER 6 | Probabilitythe prob
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164 CHAPTER 6 | Probability(Note: W
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166 CHAPTER 6 | ProbabilityFIGURE 6
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168 CHAPTER 6 | Probability■ The
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170 CHAPTER 6 | ProbabilityFinding
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172 CHAPTER 6 | Probabilityand exac
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174 CHAPTER 6 | ProbabilityFinally,
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176 CHAPTER 6 | ProbabilityXz-score
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178 CHAPTER 6 | ProbabilityBOX 6.1
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180 CHAPTER 6 | ProbabilityEXAMPLE
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182 CHAPTER 6 | ProbabilityFIGURE 6
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184 CHAPTER 6 | Probability6.5 Look
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186 CHAPTER 6 | Probability2. For a
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188 CHAPTER 6 | ProbabilityDEMONSTR
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190 CHAPTER 6 | Probability6. Draw
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Probability and Samples: TheDistrib
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SECTION 7.1 | Samples, Populations,
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SECTION 7.1 | Samples, Populations,
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SECTION 7.2 | The Distribution of S
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SECTION 7.3 | Probability and the D
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SECTION 7.3 | Probability and the D
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SECTION 7.4 | More about Standard E
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SECTION 7.4 | More about Standard E
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FOCUS ON PROBLEM SOLVING 219SUMMARY
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PROBLEMS 221STEP 2Compute the z-sco
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Introduction toHypothesis TestingCH
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SECTION 8.1 | The Logic of Hypothes
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SECTION 8.2 | Uncertainty and Error
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SECTION 8.2 | Uncertainty and Error
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SECTION 8.3 | More about Hypothesis
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SECTION 8.3 | More about Hypothesis
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SECTION 8.4 | Directional (One-Tail
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SECTION 8.5 | Concerns about Hypoth
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SECTION 8.6 | Statistical Power 255
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FOCUS ON PROBLEM SOLVING 2618. The
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PROBLEMS 263In this distribution, o
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PROBLEMS 26513. A random sample is
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Introduction to the t StatisticCHAP
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SECTION 9.1 | The t Statistic: An A
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SECTION 9.2 | Hypothesis Tests with
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SECTION 9.3 | Measuring Effect Size
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SECTION 9.4 | Directional Hypothese
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SUMMARY 2913. A researcher rejects
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DEMONSTRATION 9.1 293One-Sample Sta
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PROBLEMS 295PROBLEMS1. Under what c
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PROBLEMS 297b. Construct the 90% co
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The t Test for TwoIndependent Sampl
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SECTION 10.1 | Introduction to the
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SECTION 10.2 | The Null Hypothesis
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SECTION 10.5 | The Role of Sample V
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KEY TERMS 325SUMMARY1. The independ
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FOCUS ON PROBLEM SOLVING 327Group S
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PROBLEMS 329The t Statistic Finally
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PROBLEMS 331c. Write a sentence dem
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PROBLEMS 33319. If other factors ar
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PREVIEWIt’s the night before an e
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338 CHAPTER 11 | The t Test for Two
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PREVIEWYour job interview is tomorr
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368 CHAPTER 12 | Introduction to An
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Repeated-MeasuresAnalysis of Varian
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SECTION 13.2 | Hypothesis Testing a
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SPSS ® 4375. When the obtained F-r
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DEMONSTRATION 13.1 439you must also
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PROBLEMS 441PROBLEMS1. How does the
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PROBLEMS 44313. The following summa
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PROBLEMS 44523. The following data
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Two-FactorAnalysis of Variance(Inde
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SECTION 14.1 | An Overview of the T
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SUMMARY 473SUMMARY1. A research stu
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FOCUS ON PROBLEM SOLVING 475Descrip
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DEMONSTRATION 14.1 477STEP 2STAGE 1
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PROBLEMS 479PROBLEMS1. Define each
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PROBLEMS 48115. Research results in
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PROBLEMS 483EasyFactorA TaskDifficu
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PREVIEWA recent report describing t
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488 CHAPTER 15 | CorrelationDEFINIT
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490 CHAPTER 15 | CorrelationDEFINIT
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492 CHAPTER 15 | CorrelationSubstit
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494 CHAPTER 15 | Correlationeither
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496 CHAPTER 15 | Correlationreliabl
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498 CHAPTER 15 | Correlation60Numbe
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500 CHAPTER 15 | CorrelationOne of
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502 CHAPTER 15 | CorrelationBOX 15.
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504 CHAPTER 15 | Correlation171615Z
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506 CHAPTER 15 | Correlation3. What
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508 CHAPTER 15 | Correlationon the
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510 CHAPTER 15 | CorrelationLEARNIN
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512 CHAPTER 15 | CorrelationScoresR
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514 CHAPTER 15 | CorrelationThe pro
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516 CHAPTER 15 | Correlationthat a
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518 CHAPTER 15 | Correlationmeasure
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520 CHAPTER 15 | CorrelationSUMMARY
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522 CHAPTER 15 | CorrelationTo comp
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524 CHAPTER 15 | CorrelationSTEP 2C
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526 CHAPTER 15 | Correlation14. Ide
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Introduction to RegressionCHAPTER16
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SECTION 16.1 | Introduction to Line
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SECTION 16.3 | Introduction to Mult
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KEY TERMS 553a predicted portion an
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DEMONSTRATION 16.1 555DEMONSTRATION
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PROBLEMS 557Alzheimer’s disease.
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The Chi-Square Statistic:Tests for
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SUMMARY 591With df = 2 and α = .05
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SPSS ® SPSS ® 593General instruct
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DEMONSTRATION 17.1 595FOCUS ON PROB
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PROBLEMS 597Finally, we can add the
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PROBLEMS 599response, a sample of 1
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PREVIEWIn 1960, Gibson and Walk des
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606 CHAPTER 18 | The Binomial Testp
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608 CHAPTER 18 | The Binomial Test2
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610 CHAPTER 18 | The Binomial Test
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612 CHAPTER 18 | The Binomial Test
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614 CHAPTER 18 | The Binomial TestT
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616 CHAPTER 18 | The Binomial Testt
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618 CHAPTER 18 | The Binomial TestB
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Basic Mathematics ReviewAPPENDIXAPR
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Page 667: APPENDIX A | Basic Mathematics Revi
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Page 686 and 687: 664 APPENDIX C | Solutions for Odd-
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Page 724 and 725: 702 Statistics Organizer: Finding t
Page 739 and 740: ReferencesAckerman, R. (2011). Meta
Page 741 and 742: REFERENCES 719Alzheimer’s disease
Page 743: REFERENCES 721of aging and estrogen
Page 746 and 747: 724 NAME INDEXKaell, A., 622Kahn, K
Page 748 and 749: 726 SUBJECT INDEXConfidence interva
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728 SUBJECT INDEXIndependent random
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730 SUBJECT INDEXResearch studies,
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732 SUBJECT INDEXTwo-factor ANOVA (
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Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

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