Rubi Luneta
2081276
Tilburg University
SPSS
The Basics
Correlation: continuous + continuous variables
ANOVA: continuous + categorical variables
File → New → Syntax
Analyze > Descriptive Statistics > Frequencies
Analyze > Descriptive Statistics > Descriptives
Mean, standard deviation, minimum score, and maximum score
Analyze > Compare Means
Dependent list Y
Layer 1 of 1 X
ANOVA
The assumptions of an ANOVA are:
⁃ Correct measurement level of the X and Y variables
⁃ Normal distribution of scores on the Y variable (for the full dataset, and within each group)
⁃ No outliers
1
, ⁃ Approximately equal variances in all the groups
⁃ The observations should be independent (within- and between groups)
The normality assumption of the Y variable
Graphs > Legacy Dialogs > Histogram > Display normal curve
Variable box Y
Columns box X
Analyze > Compare Means > One-Way ANOVA > Options > Homogeneity of variance test
Dependent list Y
Factor X
The value of the F statistic
The signi cance value of the Levene Statistic
Levene Statistic
Sig.
Pearson Correlation
Since both of these variables are continuous, a suitable approach would be to investigate whether these two variables are
linearly related through a correlation.
We use histograms to check whether the assumption of normality is met and scatter plots to spot (bivariate) outliers.
The assumptions of a correlation are:
⁃ No bivariate outliers
Graphs > Legacy Dialog > Scatter/Dot… > Choose Simple Scatter > Click De ne
Analyze > Correlate > Bivariate
The signi cance of the association
2
fi fi
2081276
Tilburg University
SPSS
The Basics
Correlation: continuous + continuous variables
ANOVA: continuous + categorical variables
File → New → Syntax
Analyze > Descriptive Statistics > Frequencies
Analyze > Descriptive Statistics > Descriptives
Mean, standard deviation, minimum score, and maximum score
Analyze > Compare Means
Dependent list Y
Layer 1 of 1 X
ANOVA
The assumptions of an ANOVA are:
⁃ Correct measurement level of the X and Y variables
⁃ Normal distribution of scores on the Y variable (for the full dataset, and within each group)
⁃ No outliers
1
, ⁃ Approximately equal variances in all the groups
⁃ The observations should be independent (within- and between groups)
The normality assumption of the Y variable
Graphs > Legacy Dialogs > Histogram > Display normal curve
Variable box Y
Columns box X
Analyze > Compare Means > One-Way ANOVA > Options > Homogeneity of variance test
Dependent list Y
Factor X
The value of the F statistic
The signi cance value of the Levene Statistic
Levene Statistic
Sig.
Pearson Correlation
Since both of these variables are continuous, a suitable approach would be to investigate whether these two variables are
linearly related through a correlation.
We use histograms to check whether the assumption of normality is met and scatter plots to spot (bivariate) outliers.
The assumptions of a correlation are:
⁃ No bivariate outliers
Graphs > Legacy Dialog > Scatter/Dot… > Choose Simple Scatter > Click De ne
Analyze > Correlate > Bivariate
The signi cance of the association
2
fi fi
