Analyzing Data

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Statistically analyzing and interpreting your collected data


Data Screening

Missing Values
- Why do missing values occur?
- Why is missing data a problem?
- How do I identify if missing values are random or non-random?
- How do I deal with missing data?

- What are outliers?
- Should I check for outliers?
- How can I tell if outliers are influencing my data?
- How do I detect univariate outliers in my data?
- How do I detect bivariate and multivariate outliers in my data?
- How do I deal with outliers?

- What is "normality"?
- Why is normality important?
- How do I determine whether my data are normal?
- How do I deal with non-normality?
- How do I transform variables?

  • Statistical Tests

- Meta-analysis
- Mediation
- What is an Interaction?
- Interaction between two continuous variables
- Interaction between categorical and continuous variables
- What is a correlation?
- What is a partial correlation?
- What is a point-biserial correlation?
- What is regression?
- What is a probabilistic causal analysis?
- What is analysis of covariance (ANCOVA)?

  • Other

- What is a scatterplot?
- What is linearity?
- Want help using SPSS?
- What is "syntax" in SPSS?
- What is Computational Modeling?
- What is a rank-based nonparametric test?

  • Transforming continuous into categorical variables

- Why transform continuous variables into categorical variables?
- How to dichotomize variables?
- Why cut into thirds or fourths instead of dichotomizing?

  • Composites

- How do I create a composite of items?
- Why create a composite of items?
- How do I know when it is appropriate to create a composite?
- How do I create a composite with items with different scale ranges?
- How do I create a composite with items labeled in opposite directions?

  Overview   Research Idea   Research Design   Collecting Data   Analyzing Data   Writing a Paper  
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