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4. The fi gures are then added to give: Total = 53.65 So c 2 is 53.65 (53.7). CHAPTER 9 Measures of association 267 The degrees of freedom (DF) is one less than the number of categories, so in this case DF = 3. We need to know this, for it is usual to report the DF, along with the value of c 2 and the associated probability level. The c 2 value of 53.65 is rounded up to 53.7. This value is then compared with the value that would be expected, for a c 2 with 3 DF, if the null hypothesis were true (i.e. all brands are preferred equally). We do not have to make this comparison, as the statistical package does it for us. SPSS: one-variable g 2 If you have your data in the form of frequency counts in a table such as the one we have used for the example above, then you can enter data for the chocolate bars into SPSS as follows: ▲
268 Statistics without maths for psychology Whenever we enter the data in this way, and perform g 2 , we have to weight the cases by the frequency count. This is done in order to ‘tell’ SPSS that our data are in the form of frequency counts (rather than raw data), and is accomplished as follows: This opens the Weight Cases dialogue box, below:
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Statistics Without Maths for Psycho
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British Psychological Society stand
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Pearson Education Limited Edinburgh
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Brief contents Preface xvii Acknowl
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x Contents 3.3 Sampling error 48 SP
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xii Contents 8.3 Power 248 8.4 Fact
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xiv Contents 14 Introduction to fac
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Supporting resources Visit www.pear
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xviii Preface Although we have upda
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xx Preface of each chapter there is
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xxii Acknowledgements inferences, J
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Guided tour of the book and website
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xxvi Guided tour of the book and we
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CHAPTER OVERVIEW CHAPTER 1 Variable
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CHAPTER 1 Variables and research de
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Discussion point Dichotomising cont
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1.3 Levels of measurement CHAPTER 1
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Definition CHAPTER 1 Variables and
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Definition Activity 1.3 1.5.2 Betwe
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CHAPTER OVERVIEW CHAPTER 2 Introduc
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CHAPTER 2 Introduction to SPSS 27 Y
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CHAPTER 2 Introduction to SPSS 29 I
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CHAPTER 2 Introduction to SPSS 31 O
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CHAPTER 2 Introduction to SPSS 33 Y
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CHAPTER 2 Introduction to SPSS 35 2
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CHAPTER 2 Introduction to SPSS 37 C
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2.7 Within-participants designs CHA
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CHAPTER OVERVIEW CHAPTER 3 Descript
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Definitions CHAPTER 3 Descriptive s
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Definition CHAPTER 3 Descriptive st
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CHAPTER 3 Descriptive statistics 47
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Activity 3.4 CHAPTER 3 Descriptive
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3.4 Graphically describing data Def
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Figure 3.3 Histogram of the depress
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Figure 3.5 Example of a stem and le
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3.5 Scattergrams Definition CHAPTER
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SPSS: generating scattergrams CHAPT
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3.7 The normal distribution CHAPTER
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3.8.1 The range CHAPTER 3 Descripti
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SPSS: obtaining measures of variati
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Figure 3.25 Bimodal distribution CH
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Activity 3.9 Which of the following
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Summary CHAPTER 3 Descriptive stati
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Multiple choice questions 1. Which
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12. What is the mean of the followi
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References Armitage, C. and Reidy,
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CHAPTER 4 Probability, sampling and
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Definition CHAPTER 4 Probability, s
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Activity 4.6 CHAPTER 4 Probability,
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Activity 4.8 CHAPTER 4 Probability,
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Figure 4.22 Error bar chart for a d
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Exercise 2 CHAPTER 4 Probability, s
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References Åberg, M.A.I., Pedersen
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CHAPTER 5 Hypothesis testing and st
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Definition CHAPTER 5 Hypothesis tes
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Discussion point CHAPTER 5 Hypothes
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Definitions CHAPTER 5 Hypothesis te
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Discussion point Why report the exa
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Example from the literature CHAPTER
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5.10 Why set E at 0.05? CHAPTER 5 H
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Figure 5.7 Illustration of scores i
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Figure 5.11 Flow diagram as a guide
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6. Convert the fi rst score from ea
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6.1 Bivariate correlations CHAPTER
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Figure 6.1 Sister’s age and your
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CHAPTER 6 Correlational analysis: P
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Activity 6.2 CHAPTER 6 Correlationa
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Activity 6.4 CHAPTER 6 Correlationa
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Figure 6.13 Perfect linear relation
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This brings you to the following di
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Activity 6.8 Look at the following
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SPSS: obtaining a scattergram matri
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Personal reflection Emeritus Profes
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Activity 6.10 CHAPTER 6 Correlation
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Summary CHAPTER 6 Correlational ana
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Multiple choice questions CHAPTER 6
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Which is the most sensible answer?
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CHAPTER OVERVIEW CHAPTER 7 Analyses
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CHAPTER 7 Analyses of differences b
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CHAPTER 7 Analyses of differences b
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10.7.3 Post-hoc tests/planned CHAPT
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Figure 10.5 Mean symptom severity r
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CHAPTER 10 Analysis of differences
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2. Which is the most appropriate co
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CHAPTER 10 Analysis of differences
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Which is the most appropriate state
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T-TEST CHAPTER 11 Analysis of varia
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11.6.3 Effect size CHAPTER 11 Analy
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Example from the literature Attenti
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Click on the Defi ne button and set
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SPSS exercises Exercise 1 CHAPTER 1
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2. ANOVA is useful for: (a) Teasing
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References Baron-Cohen, S., Wheelwr
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CHAPTER 12 Regression analysis 385
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Figure 12.2 Scatterplot with line o
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Ensuring that the Linear option is
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Figure 12.5 Plot of x with y CHAPTE
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Figure 12.7 Plot of x with y CHAPTE
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Figure 12.8 Plot of sales against p
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SPSS: linear regression analysis Se
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Variance explained CHAPTER 12 Regre
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R 2 CHAPTER 12 Regression analysis
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Y (predicted examination success) =
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Personal reflection Article: Barrie
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Summary • Regression analysis all
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Multiple choice questions 1. The li
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10. The correlation between credit
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20. Which is the most appropriate s
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Example CHAPTER 13 Analysis partial
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This gives you the following dialog
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CHAPTER 13 Analysis partialling out
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Figure 13.4 Regression lines for ea
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In addition, for most purposes: CHA
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Figure 13.11 Regression lines for t
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SPSS: obtaining output for an ANCOV
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Figure 13.12 Regression lines for e
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Activity 13.4 ANCOVA assumes that:
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SPSS exercise CHAPTER 13 Analysis p
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5. The covariate is: (a) Beginning
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Questions 16 to 20 relate to the fo
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CHAPTER OVERVIEW CHAPTER 14 Introdu
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Activity 14.1 CHAPTER 14 Introducti
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Figure 14.1 Ten correlated variable
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CHAPTER 14 Introduction to factor a
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CHAPTER 14 Introduction to factor a
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608 z-score Statistics without math
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612 Index autism-like traits 348 av
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614 Index expected frequencies 265,
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616 Index mental health procrastina
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618 Index sample size 250 - 2, 253
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620 Index Weight Cases dialogue box
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