Learning statistics with Jamovi
Subtitle: a tutorial for beginners in statistical analysis
By: Danielle J. Navarro and David R. Foxcroft
Publisher: Open Book Publishers
Published: 2025
Place of publication: Cambridge, UK
Language: eng
Number of pages: 476
ISBN-13: 9781800649392; 9781800649378; 9781800649385
Subjects: Textbooks; Statistics; Jamovi (Computer file)
Notes: Includes bibliographical references (pages 443-446).

Creative Commons * https://creativecommons.org/licenses/*

Description based on online resource; title from PDF title page (Open Book Publishers website; viewed on 2025-01-24).
Table of contents: title: Preface
pagenum: 1; label: I
title: Beginnings
pagenum: 3; label: 1
title: Why do we learn statistics
pagenum: 3; label: 1.1
title: On the psychology of statistics
pagenum: 5; label: 1.1.1
title: The curse of belief bias
pagenum: 6; label: 1.2
title: The cautionary tale of Simpson's paradox
pagenum: 8; label: 1.3
title: Statistics in psychology
pagenum: 11; label: 1.4
title: Statistics in everyday life
pagenum: 13; label: 1.5
title: There's more to research methods than statistics
pagenum: 13; label: 2
title: A brief introduction to research design
pagenum: 15; label: 2.1
title: Introduction to psychological measurement
pagenum: 15; label: 2.1.1
title: Some thoughts about psychological measurement
pagenum: 15; label: 2.1.2
title: Operationalisation: Defining your measurement
pagenum: 17; label: 2.2
title: Scales of measurement
pagenum: 18; label: 2.2.1
title: Nominal scale
pagenum: 18; label: 2.2.2
title: Ordinal scale
pagenum: 19; label: 2.2.3
title: Interval scale
pagenum: 20; label: 2.2.4
title: Ratio scale
pagenum: 21; label: 2.2.5
title: Continuous versus discrete variables
pagenum: 21; label: 2.2.6
title: Some complexities
pagenum: 22; label: 2.3
title: Assessing the reliability of a measurement
pagenum: 23; label: 2.4
title: The "role" of variables: predictors and outcomes
pagenum: 25; label: 2.5
title: Experimental and non-experimental research
pagenum: 25; label: 2.5.1
title: Experimental research
pagenum: 26; label: 2.5.2
title: Non-experimental research
pagenum: 26; label: 2.6
title: Assessing the validity of a study
pagenum: 27; label: 2.6.1
title: Internal validity
pagenum: 28; label: 2.6.2
title: External validity
pagenum: 28; label: 2.6.3
title: Construct validity
pagenum: 29; label: 2.6.4
title: Face validity
pagenum: 30; label: 2.6.5
title: Ecological validity
pagenum: 30; label: 2.7
title: Confounders, artefacts and other threats to validity
pagenum: 31; label: 2.7.1
title: History effects
pagenum: 32; label: 2.7.2
title: Maturation effects
pagenum: 32; label: 2.7.3
title: Repeated testing effects
pagenum: 33; label: 2.7.4
title: Selection bias
pagenum: 33; label: 2.7.5
title: Differential attrition
pagenum: 33; label: 2.7.6
title: Non-response bias
pagenum: 34; label: 2.7.7
title: Regression to the mean
pagenum: 35; label: 2.7.8
title: Experimenter bias
pagenum: 36; label: 2.7.9
title: Demand effects and reactivity
pagenum: 37; label: 2.7.10
title: Placebo effects
pagenum: 37; label: 2.7.11
title: Situation, measurement and sub-population effects
pagenum: 38; label: 2.7.12
title: Fraud, deception and self-deception
pagenum: 38; label: 2.8
title: Summary
pagenum: 40; label: II
title: An introduction to jamovi
pagenum: 43; label: 3
title: Getting started with jamovi
pagenum: 45; label: 3.1
title: Installing jamovi
pagenum: 46; label: 3.1.1
title: Starting up jamovi
pagenum: 46; label: 3.2
title: Analyses
pagenum: 47; label: 3.3
title: The spreadsheet
pagenum: 48; label: 3.3.1
title: Variables
pagenum: 48; label: 3.3.2
title: Computed variables
pagenum: 49; label: 3.3.3
title: Copy and paste
pagenum: 50; label: 3.3.4
title: Syntax mode
pagenum: 50; label: 3.4
title: Loading data in jamovi
pagenum: 51; label: 3.4.1
title: Importing data from csv files
pagenum: 51; label: 3.5
title: Importing unusual data files
pagenum: 52; label: 3.5.1
title: Loading data from text files
pagenum: 53; label: 3.5.2
title: Loading data from SPSS (and other statistics packages)
pagenum: 53; label: 3.5.3
title: Loading Excel files
pagenum: 54; label: 3.6
title: Changing data from one level to another
pagenum: 54; label: 3.7
title: Installing add-on modules into jamovi
pagenum: 54; label: 3.8
title: Quitting jamovi
pagenum: 55; label: 3.9
title: Summary
pagenum: 55; label: III
title: Working with data
pagenum: 57; label: 4
title: Descriptive statistics
pagenum: 59; label: 4.1
title: Measures of central tendency
pagenum: 60; label: 4.1.1
title: The mean
pagenum: 61; label: 4.1.2
title: Calculating the mean in jamovi
pagenum: 61; label: 4.1.3
title: The median
pagenum: 62; label: 4.1.4
title: Mean or median? What's the difference?
pagenum: 63; label: 4.1.5
title: A real-life example
pagenum: 64; label: 4.1.6
title: Mode
pagenum: 65; label: 4.2
title: Measures of variability
pagenum: 67; label: 4.2.1
title: Range
pagenum: 68; label: 4.2.2
title: Interquartile range
pagenum: 68; label: 4.2.3
title: Mean absolute deviation
pagenum: 69; label: 4.2.4
title: Variance
pagenum: 70; label: 4.2.5
title: Standard deviation
pagenum: 73; label: 4.2.6
title: Which measure to use?
pagenum: 73; label: 4.3
title: Skew and kurtosis
pagenum: 74; label: 4.4
title: Descriptive statistics separately for each group
pagenum: 77; label: 4.5
title: Standard scores
pagenum: 78; label: 4.6
title: Summary
pagenum: 80; label: 5
title: Drawing graphs
pagenum: 81; label: 5.1
title: Histograms
pagenum: 82; label: 5.2
title: Boxplots
pagenum: 84; label: 5.2.1
title: Violin plots
pagenum: 85; label: 5.2.2
title: Drawing multiple boxplots
pagenum: 87; label: 5.2.3
title: Using box plots to detect outliers
pagenum: 87; label: 5.3
title: Bar graphs
pagenum: 89; label: 5.4
title: Saving image files using jamovi
pagenum: 90; label: 5.5
title: Summary
pagenum: 91; label: 6
title: Pragmatic matters
pagenum: 93; label: 6.1
title: Tabulating and cross-tabulating data
pagenum: 94; label: 6.1.1
title: Creating tables for single variables
pagenum: 94; label: 6.1.2
title: Adding percentages to a contingency table
pagenum: 95; label: 6.2
title: Logical expressions in jamovi
pagenum: 95; label: 6.2.1
title: Assessing mathematical truths
pagenum: 97; label: 6.2.2
title: Logical operations
pagenum: 97; label: 6.2.3
title: Applying logical operation to text
pagenum: 99; label: 6.3
title: Transforming and recoding a variable
pagenum: 100; label: 6.3.1
title: Creating a transformed variable
pagenum: 101; label: 6.3.2
title: Collapsing a variable into a smaller number of discrete levels or categories
pagenum: 103; label: 6.3.3
title: Creating a transformation that can be applied to multiple variables
pagenum: 104; label: 6.4
title: A few more mathematical functions and operations
pagenum: 107; label: 6.4.1
title: Logarithms and exponentials
pagenum: 107; label: 6.5
title: Extracting a subset of the data
pagenum: 108; label: 6.6
title: Summary
pagenum: 110; label: IV
title: Statistical theory
pagenum: 111; title: Prelude
pagenum: 113; title: On the limits of logical reasoning
pagenum: 113; title: Learning without making assumptions is a myth
pagenum: 116; label: 7
title: Introduction to probability
pagenum: 117; label: 7.1
title: How are probability and statistics different?
pagenum: 118; label: 7.2
title: What does probability mean?
pagenum: 119; label: 7.2.1
title: The frequentist view
pagenum: 120; label: 7.2.2
title: The Bayesian view
pagenum: 123; label: 7.2.3
title: What's the difference? And who is right?
pagenum: 123; label: 7.3
title: Basic probability theory
pagenum: 124; label: 7.3.1
title: Introducing probability distributions
pagenum: 124; label: 7.4
title: The binomial distribution
pagenum: 127; label: 7.4.1
title: Introducing the binomial
pagenum: 127; label: 7.5
title: The normal distribution
pagenum: 129; label: 7.5.1
title: Probability density
pagenum: 133; label: 7.6
title: Other useful distributions
pagenum: 134; label: 7.7
title: Summary
pagenum: 136; label: 8
title: Estimating unknown quantities from a sample
pagenum: 139; label: 8.1
title: Samples, populations and sampling
pagenum: 139; label: 8.1.1
title: Defining a population
pagenum: 140; label: 8.1.2
title: Simple random samples
pagenum: 141; label: 8.1.3
title: Most samples are not simple random samples
pagenum: 143; label: 8.1.4
title: How much does it matter if you don't have a simple random sample?
pagenum: 144; label: 8.1.5
title: Population parameters and sample statistics
pagenum: 145; label: 8.2
title: The law of large numbers
pagenum: 147; label: 8.3
title: Sampling distributions and the central limit theorem
pagenum: 148; label: 8.3.1
title: Sampling distribution of the mean
pagenum: 149; label: 8.3.2
title: Sampling distributions exist for any sample statistic!
pagenum: 151; label: 8.3.3
title: The central limit theorem
pagenum: 151; label: 8.4
title: Estimating population parameters
pagenum: 154; label: 8.4.1
title: Estimating the population mean
pagenum: 155; label: 8.4.2
title: Estimating the population standard deviation
pagenum: 156; label: 8.5
title: Estimating a confidence interval
pagenum: 160; label: 8.5.1
title: Interpreting a confidence interval
pagenum: 161; label: 8.5.2
title: Calculating confidence intervals in jamovi
pagenum: 163; label: 8.6
title: Summary
pagenum: 163; label: 9
title: Hypothesis testing
pagenum: 165; label: 9.1
title: A menagerie of hypotheses
pagenum: 165; label: 9.1.1
title: Research hypotheses versus statistical hypotheses
pagenum: 166; label: 9.1.2
title: Null hypotheses and alternative hypotheses
pagenum: 168; label: 9.2
title: Two types of errors
pagenum: 169; label: 9.3
title: Test statistics and sampling distributions
pagenum: 170; label: 9.4
title: Making decisions
pagenum: 171; label: 9.4.1
title: Critical regions and critical values
pagenum: 172; label: 9.4.2
title: A note on statistical "significance"
pagenum: 174; label: 9.4.3
title: The difference between one-sided and two-sided tests
pagenum: 174; label: 9.5
title: The p-value of a test
pagenum: 175; label: 9.5.1
title: A softer view of decision making
pagenum: 175; label: 9.5.2
title: The probability of extreme data
pagenum: 176; label: 9.5.3
title: A common mistake
pagenum: 177; label: 9.6
title: Reporting the results of a hypothesis test
pagenum: 177; label: 9.6.1
title: The issue
pagenum: 177; label: 9.6.2
title: Two proposed solutions
pagenum: 178; label: 9.7
title: Running the hypothesis test in practice
pagenum: 179; label: 9.8
title: Effect size, sample size and power
pagenum: 180; label: 9.8.1
title: The power function
pagenum: 181; label: 9.8.2
title: The power function
pagenum: 183; label: 9.8.3
title: Increasing the power of your study
pagenum: 184; label: 9.9
title: Some issues to consider
pagenum: 186; label: 9.9.1
title: Neyman versus Fisher
pagenum: 186; label: 9.9.2
title: Bayesians versus frequentists
pagenum: 187; label: 9.9.3
title: Traps
pagenum: 187; label: 9.10
title: Summary
pagenum: 188; label: V
title: Statistical tools
pagenum: 191; label: 10
title: Categorical data analysis
pagenum: 193; label: 10.1
title: The \(\chi^2\) (chi-square) goodness-of-fit test
pagenum: 193; label: 10.1.1
title: The cards data
pagenum: 194; label: 10.1.2
title: The null hypothesis and the alternative hypothesis
pagenum: 195; label: 10.1.3
title: The "goodness-of-fit" test statistic
pagenum: 196; label: 10.1.4
title: The sampling distribution of the GOF statistic
pagenum: 198; label: 10.1.5
title: Degrees of freedom
pagenum: 199; label: 10.1.6
title: Testing the null hypothesis
pagenum: 200; label: 10.1.7
title: Doing the test in jamovi
pagenum: 201; label: 10.1.8
title: Specifying a different null hypothesis
pagenum: 202; label: 10.1.9
title: How to report the results of the test
pagenum: 203; label: 10.2
title: The \(\chi^2\) test of independence (or association)
pagenum: 205; label: 10.2.1
title: Constructing our hypothesis test
pagenum: 206; label: 10.2.2
title: Doing the test in jamovi
pagenum: 208; label: 10.3
title: The continuity correction
pagenum: 210; label: 10.4
title: Effect size
pagenum: 210; label: 10.5
title: Assumptions of the test(s)
pagenum: 211; label: 10.6
title: The Fisher exact test
pagenum: 212; label: 10.7
title: The McNemar test
pagenum: 213; label: 10.7.1
title: Doing the McNemar test in jamovi
pagenum: 215; label: 10.8
title: What's the difference between McNemar and independence?
pagenum: 216; label: 10.9
title: Summary
pagenum: 218; label: 11
title: Comparing two means
pagenum: 219; label: 11.1
title: The one-sample z-test
pagenum: 219; label: 11.1.1
title: The inference problem that the test addresses
pagenum: 220; label: 11.1.2
title: Constructing the hypothesis test
pagenum: 221; label: 11.1.3
title: A worked example, by hand
pagenum: 224; label: 11.1.4
title: Assumptions of the z-test
pagenum: 225; label: 11.2
title: The one-sample t-test
pagenum: 225; label: 11.2.1
title: Introducing the t-test
pagenum: 226; label: 11.2.2
title: Doing the test in jamovi
pagenum: 227; label: 11.2.3
title: Assumptions of the one sample t-test
pagenum: 229; label: 11.3
title: The independent samples t-test (Student test)
pagenum: 229; label: 11.3.1
title: The data
pagenum: 229; label: 11.3.2
title: Introducing the test
pagenum: 230; label: 11.3.3
title: A "pooled estimate" of the standard deviation
pagenum: 231; label: 11.4
title: Completing the test
pagenum: 232; label: 11.4.1
title: Doing the test in jamovi
pagenum: 233; label: 11.4.2
title: Positive and negative t-values
pagenum: 234; label: 11.4.3
title: Assumptions of the Student t-test
pagenum: 235; label: 11.5
title: The independent samples t-test (Welch test)
pagenum: 236; label: 11.5.1
title: Doing the Welch test in jamovi
pagenum: 237; label: 11.5.2
title: Assumptions of the Welch test
pagenum: 238; label: 11.6
title: The paired-samples t-test
pagenum: 238; label: 11.6.1
title: The data
pagenum: 238; label: 11.6.2
title: What is the paired samples t-test?
pagenum: 240; label: 11.6.3
title: Doing the test in jamovi
pagenum: 242; label: 11.7
title: One-sided tests
pagenum: 242; label: 11.8
title: Effect size
pagenum: 244; label: 11.8.1
title: Cohen's d from one sample
pagenum: 245; label: 11.8.2
title: Cohen's d from a Student's t-test
pagenum: 245; label: 11.8.3
title: Cohen's d from a paired-samples test
pagenum: 246; label: 11.9
title: Checking the normality of a sample
pagenum: 247; label: 11.9.1
title: QQ plots
pagenum: 247; label: 11.9.2
title: QQ plots for independent and paired t-tests
pagenum: 248; label: 11.9.3
title: Shapiro-Wilk tests
pagenum: 248; label: 11.9.4
title: Example
pagenum: 251; label: 11.10
title: Testing non-normal data
pagenum: 251; label: 11.10.1
title: Two sample Mann-Whitney U test
pagenum: 252; label: 11.10.2
title: One sample Wilcoxon test
pagenum: 253; label: 11.11
title: Summary
pagenum: 254; label: 12
title: Correlation and linear regression
pagenum: 255; label: 12.1
title: Correlations
pagenum: 255; label: 12.1.1
title: The data
pagenum: 255; label: 12.1.2
title: The strength and direction of a relationship
pagenum: 256; label: 12.1.3
title: The correlation coefficient
pagenum: 258; label: 12.1.4
title: Calculating correlations in jamovi
pagenum: 258; label: 12.1.5
title: Interpreting a correlation
pagenum: 258; label: 12.1.6
title: Spearman's rank correlations
pagenum: 260; label: 12.2
title: Scatterplots
pagenum: 263; label: 12.2.1
title: More elaborate options
pagenum: 265; label: 12.3
title: What is a linear regression model?
pagenum: 265; label: 12.4
title: Estimating a linear regression model
pagenum: 268; label: 12.4.1
title: Linear regression in jamovi
pagenum: 270; label: 12.4.2
title: Interpreting the estimated model
pagenum: 270; label: 12.5
title: Multiple linear regression
pagenum: 271; label: 12.5.1
title: Doing it in jamovi
pagenum: 271; label: 12.6
title: Quantifying the fit of the regression model
pagenum: 273; label: 12.6.1
title: The R2 value
pagenum: 273; label: 12.6.2
title: The relationship between regression and correlation
pagenum: 274; label: 12.6.3
title: The adjusted R2 value
pagenum: 274; label: 12.7
title: Hypothesis tests for regression models
pagenum: 275; label: 12.7.1
title: Testing the model as a whole
pagenum: 275; label: 12.7.2
title: Tests for individual coefficients
pagenum: 275; label: 12.7.3
title: Running the hypothesis tests in jamovi
pagenum: 276; label: 12.8
title: Regarding regression coefficients
pagenum: 277; label: 12.8.1
title: Confidence intervals for the coefficients
pagenum: 278; label: 12.8.2
title: Calculating standardised regression coefficients
pagenum: 278; label: 12.9
title: Assumptions of regression
pagenum: 279; label: 12.10
title: Model checking
pagenum: 280; label: 12.10.1
title: Three kinds of residuals
pagenum: 281; label: 12.10.2
title: Checking the linearity of the relationship
pagenum: 281; label: 12.10.3
title: Checking the normality of the residuals
pagenum: 283; label: 12.10.4
title: Checking equality of variance
pagenum: 285; label: 12.10.5
title: Checking for collinearity
pagenum: 286; label: 12.10.6
title: Outliers and anomalous data
pagenum: 286; label: 12.11
title: Model selection
pagenum: 290; label: 12.11.1
title: Backward elimination
pagenum: 291; label: 12.11.2
title: Forward selection
pagenum: 292; label: 12.11.3
title: A caveat
pagenum: 292; label: 12.11.4
title: Comparing two regression models
pagenum: 293; label: 12.12
title: Summary
pagenum: 294; label: 13
title: Comparing several means (one-way ANOVA)
pagenum: 295; label: 13.1
title: An illustrative data set
pagenum: 295; label: 13.2
title: How ANOVA works
pagenum: 297; label: 13.2.1
title: Two formulas for the variance of Y
pagenum: 297; label: 13.2.2
title: From variances to sums of squares
pagenum: 299; label: 13.2.3
title: From sums of squares to the F-test
pagenum: 300; label: 13.2.4
title: A worked example
pagenum: 301; label: 13.3
title: Running an ANOVA in jamovi
pagenum: 305; label: 13.3.1
title: Using jamovi to specify your ANOVA
pagenum: 305; label: 13.4
title: Effect size
pagenum: 306; label: 13.5
title: Multiple comparisons and post hoc tests
pagenum: 307; label: 13.5.1
title: Running "pairwise" t-tests
pagenum: 308; label: 13.5.2
title: Corrections for multiple testing
pagenum: 308; label: 13.5.3
title: Bonferroni corrections
pagenum: 309; label: 13.5.4
title: Holm corrections
pagenum: 309; label: 13.5.5
title: Writing up the post hoc test
pagenum: 310; label: 13.6
title: The assumptions of one-way ANOVA
pagenum: 311; label: 13.6.1
title: Checking the homogeneity of variance assumption
pagenum: 311; label: 13.6.2
title: Running the Levene test in jamovi
pagenum: 312; label: 13.6.3
title: Removing the homogeneity of variance assumption
pagenum: 312; label: 13.6.4
title: Checking the normality assumption
pagenum: 313; label: 13.6.5
title: Removing the normality assumption
pagenum: 314; label: 13.6.6
title: The logic behind the Kruskal-Wallis test
pagenum: 315; label: 13.6.7
title: Additional details
pagenum: 315; label: 13.6.8
title: How to run the Kruskal-Wallis test in jamovi
pagenum: 315; label: 13.7
title: Repeated measures one-way ANOVA
pagenum: 316; label: 13.7.1
title: Repeated measures ANOVA in jamovi
pagenum: 317; label: 13.8
title: The Friedman non-parametric repeated measures ANOVA test
pagenum: 321; label: 13.9
title: On the relationship between ANOVA and the Student t-test
pagenum: 322; label: 13.10
title: Summary
pagenum: 322; label: 14
title: Factorial ANOVA
pagenum: 325; label: 14.1
title: Factorial ANOVA 1: balanced designs, focus on main effects
pagenum: 325; label: 14.1.1
title: What hypotheses are we testing?
pagenum: 326; label: 14.1.2
title: Running the analysis in jamovi
pagenum: 329; label: 14.1.3
title: How are the sum of squares calculated?
pagenum: 331; label: 14.1.4
title: What are our degrees of freedom?
pagenum: 332; label: 14.1.5
title: Factorial ANOVA versus one-way ANOVAs
pagenum: 332; label: 14.1.6
title: What kinds of outcomes does this analysis capture?
pagenum: 333; label: 14.2
title: Factorial ANOVA 2: balanced designs, interpreting interactions
pagenum: 333; label: 14.2.1
title: What exactly is an interaction effect?
pagenum: 336; label: 14.2.2
title: Degrees of freedom for the interaction
pagenum: 336; label: 14.2.3
title: Running the ANOVA in jamovi
pagenum: 337; label: 14.2.4
title: Interpreting the results
pagenum: 337; label: 14.3
title: Effect size
pagenum: 339; label: 14.3.1
title: Estimated group means
pagenum: 340; label: 14.4
title: Assumption checking
pagenum: 342; label: 14.4.1
title: Homogeneity of variance
pagenum: 343; label: 14.4.2
title: Normality of residuals
pagenum: 343; label: 14.5
title: Analysis of covariance (ANCOVA)
pagenum: 343; label: 14.5.1
title: Running ANCOVA in jamovi
pagenum: 345; label: 14.6
title: ANOVA as a linear model
pagenum: 348; label: 14.6.1
title: Some data
pagenum: 348; label: 14.6.2
title: ANOVA with binary factors as a regression model
pagenum: 349; label: 14.6.3
title: How to encode non binary factors as contrasts
pagenum: 353; label: 14.6.4
title: The equivalence between ANOVA and regression for non-binary factors
pagenum: 355; label: 14.6.5
title: Degrees of freedom as parameter counting!
pagenum: 357; label: 14.7
title: Different ways to specify contrasts
pagenum: 358; label: 14.7.1
title: Treatment contrasts
pagenum: 359; label: 14.7.2
title: Helmert contrasts
pagenum: 359; label: 14.7.3
title: Sum to zero contrasts
pagenum: 360; label: 14.7.4
title: Optional contrasts in jamovi
pagenum: 361; label: 14.8
title: Post hoc tests
pagenum: 361; label: 14.9
title: The method of planned comparisons
pagenum: 364; label: 14.10
title: Factorial ANOVA 3: unbalanced designs
pagenum: 365; label: 14.10.1
title: The coffee data
pagenum: 366; label: 14.10.2
title: "Standard ANOVA" does not exist for unbalanced designs
pagenum: 367; label: 14.10.3
title: Type I sum of squares
pagenum: 367; label: 14.10.4
title: Type III sum of squares
pagenum: 370; label: 14.10.5
title: Type II sum of squares
pagenum: 372; label: 14.10.6
title: Effect sizes (and non-additive sums of squares)
pagenum: 375; label: 14.11
title: Summary
pagenum: 376; label: 15
title: Factor Analysis
pagenum: 377; label: 15.1
title: Exploratory Factor Analysis
pagenum: 377; label: 15.1.1
title: Checking assumptions
pagenum: 379; label: 15.1.2
title: What is EFA good for?
pagenum: 379; label: 15.1.3
title: EFA in jamovi
pagenum: 380; label: 15.1.4
title: Writing up an EFA
pagenum: 390; label: 15.2
title: Principal Component Analysis
pagenum: 391; label: 15.3
title: Confirmatory Factor Analysis
pagenum: 392; label: 15.3.1
title: CFA in jamovi
pagenum: 394; label: 15.3.2
title: Reporting a CFA
pagenum: 400; label: 15.4
title: Multi-Trait Multi-Method CFA
pagenum: 401; label: 15.4.1
title: MTMM CFA in jamovi
pagenum: 405; label: 15.5
title: Internal consistency reliability analysis
pagenum: 407; label: 15.5.1
title: Reliability analysis in jamovi
pagenum: 409; label: 15.6
title: Summary
pagenum: 411; label: VI
title: Endings, alternatives and prospects
pagenum: 413; label: 16
title: Bayesian statistics
pagenum: 415; label: 16.1
title: Probabilistic reasoning by rational agents
pagenum: 415; label: 16.1.1
title: Priors: what you believed before
pagenum: 416; label: 16.1.2
title: Likelihoods: theories about the data
pagenum: 416; label: 16.1.3
title: The joint probability of data and hypothesis
pagenum: 417; label: 16.1.4
title: Updating beliefs using Bayes' rule
pagenum: 419; label: 16.2
title: Bayesian hypothesis tests
pagenum: 420; label: 16.2.1
title: The Bayes factor
pagenum: 421; label: 16.2.2
title: Interpreting Bayes factors
pagenum: 422; label: 16.3
title: Why be a Bayesian?
pagenum: 423; label: 16.3.1
title: Statistics that mean what you think they mean
pagenum: 423; label: 16.3.2
title: Evidentiary standards you can believe
pagenum: 424; label: 16.3.3
title: The p-value is a lie.
pagenum: 425; label: 16.3.4
title: Is it really this bad?
pagenum: 429; label: 16.4
title: Bayesian t-tests
pagenum: 430; label: 16.4.1
title: Independent samples t-test
pagenum: 430; label: 16.4.2
title: Paired samples t-test
pagenum: 431; label: 16.5
title: Summary
pagenum: 432; title: Epilogue
pagenum: 433; title: The undiscovered statistics
pagenum: 433; title: Omissions within the topics covered
pagenum: 433; title: Statistical models missing from the book
pagenum: 434; title: Other ways of doing inference
pagenum: 437; title: Miscellaneous topics
pagenum: 439; title: Learning the basics, and learning them in jamovi
pagenum: 441; title: References
pagenum: 443; title: Chapter notes
pagenum: 447; title: About the team
pagenum: 475