1. Using SPSS
1.1. Descriptive statistics
1.2. Frequency tables
1.3. Making graphs
1.3.1. Graphical Displays
1.3.1.1. Single continuous variable
1.3.1.1.1. Histogram
1.3.1.1.2. Boxplot
1.3.1.2. Single Categorical Variable
1.3.1.2.1. Pie Chart
1.3.1.2.2. Bar Chart
1.3.1.3. Continuous and Categorical Variable
1.3.1.3.1. Side-by-side boxplot
1.3.1.3.2. Error bar plot
1.3.1.4. Multiple Continuous Variable
1.3.1.4.1. Scatterplot
2. Incidental Learning
2.1. Transforming data (Log10)
2.2. Pearson vs Spearman's Rho (and relative assumptions)
2.3. ANOVA
2.4. Lack of linear correlation
3. Hypothesis testing
3.1. Null hypothesis and Alternative hipothesis
3.2. Type I error, Type II error, and Power
3.3. Null hypothesis, significance testing (NHST), and p-value
3.4. One sample T-test
3.5. T-tests
3.5.1. One sample T-Test
3.5.1.1. Compare sample mean with population mean
3.5.2. Independent Sample T-test
3.5.2.1. Compare means of 2 independent samples
3.5.3. Dependent Sample T-Test
3.5.3.1. Compare means of 2 dependent/paired samples
4. Correlation
4.1. Pearson Correlation
4.1.1. Assumptions
4.1.1.1. Only for continuous variables
4.1.1.2. Must be linear
4.1.1.3. Homoscedasticity
4.2. Spearman
4.2.1. Assumptions
4.2.1.1. For continuous and ordinal variables
5. Research process
5.1. Verify the research question
5.1.1. Types of variables
5.1.1.1. Categorical
5.1.1.1.1. Nominal
5.1.1.1.2. Ordinal
5.1.1.2. Continuous
5.1.1.2.1. Interval
5.1.1.2.2. Ratio
5.1.2. Measurement error
5.1.2.1. Random error
5.1.2.2. Systematic error (bias)
5.2. Data collection
5.2.1. Correlational Research - observational
5.2.2. Experimental Research
5.2.2.1. Between subject design
5.2.2.2. Within subject design