The Research Process
Types of statistical models
Populations and samples
Simple statistical models
The mean as a model
The variance and standard deviation
Central Limit Theorem
The standard error
Non-significant results and Significant results:
One- and two-tailed tests
Type I and Type II errors
To explore the key windows in SPSS
The syntax editor
How to create variables
Enter Data and adjust the properties of your variables
How to Load Files and Save
Opening Excel Files
Deleting/Inserting a Case or a Column
Using SPSS Help
The art of presenting data
The SPSS Chart Builder
Histograms: a good way to spot obvious problems
Boxplots (box–whisker diagrams)
Graphing means: bar charts and error bars
Simple bar charts for independent means
Graphing relationships: the scatterplot
Simple and grouped -D scatterplots
Simple dot plot or density plot
Type I and Type II errors
What are assumptions?
Assumptions of parametric data
The assumption of normality
Quantifying normality with numbers
Exploring groups of data
Testing whether a distribution is normal
Kolmogorov–Smirnov test on SPSS
Testing for homogeneity of variance
Correcting problems in the data
Looking at relationships
Standardization and the correlation coefficient
The significance of the correlation coefficient
Confidence intervals for r
Comparing independent rs
Calculating the effect size
How to report correlation coefficients
An introduction to regression
Some important information about straight lines
The method of least squares
Assessing the goodness of fit: sums of squares, R and R2
Doing simple regression on SPSS
Multiple regression: the basics
How to do multiple regression using SPSS
Background to logistic regression
What are the principles behind logistic regression?
Assessing the model: the log-likelihood statistic
Assessing the model: R and R2
Methods of logistic regression
Interpreting logistic regression
How to report logistic regression
Predicting several categories: multinomial logistic regression
Running multinomial logistic regression in SPSS
Looking at differences
Rationale for the t-test
Reporting the dependent t-test
Reporting the independent t-test
Between groups or repeated measures?
The t-test as a general linear model
Comparing several means : ANOVA (GLM)
The theory behind ANOVA
The theory behind ANOVA
Inflated error rates
ANOVA as regression
Assumptions of ANOVA
Post hoc procedure
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