An exploratory analysis is a statistical test undertaken without a pre-existing hypothesis to discover unexpected relationships or interesting patterns in the data. Researchers conduct these analyses after completing their planned analyses to find new patterns that might provide the basis for future research.

Exploratory Analysis

Common planned analyses depend on the research design. For anticipated differences between groups, researchers might calculate means and standard deviations, create bar graphs, and compute Cohen's $$d$$. For expected correlations, they might generate scatterplots or line graphs, check for nonlinearity and restriction of range, and calculate Pearson's $$r$$.

Planned Analysis Example

Which of the following best describes a planned analysis in psychological research?

A planned analysis is a statistical test conducted to evaluate a specific relationship or difference that was expected in the researcher's original hypothesis. For example, computing means and a Cohen's $$d$$ to test an expected difference between conditions, or calculating Pearson's $$r$$ for an anticipated correlation, are planned analyses.

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Once experimental data is collected across different groups, it undergoes statistical analysis. This crucial process determines if the observed outcome differences between the testing conditions are meaningful, systematic, and genuinely related to the independent variable rather than being due to random chance.

Statistical Analysis

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KPU Research Methods in Psychology - 4th American Edition

Planned Analysis

Descriptive statistics are a set of quantitative techniques used to summarize, organize, and visually display the data collected from a research sample. Important examples include measures of central tendency (such as the mean, median, and mode), which describe average scores, and measures of dispersion (such as the range, standard deviation, and variance), which indicate how spread apart the scores are.

Descriptive Statistics

Inferential statistics are a set of mathematical techniques used by researchers to determine whether a statistical result or relationship observed in a study's sample reflects something that is genuinely true of the broader population.

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