Statistics in Psychology Research

Data Visualization

• Data visualization helps identify patterns, trends, or relationships in data and assesses the strength and direction of correlations.
• It also helps identify outliers or clusters within the data set.

Ethics in Statistical Analysis

• Ethics ensure that research is conducted responsibly, with respect for the rights and well-being of participants.
• It involves obtaining informed consent, protecting participant confidentiality, minimizing harm and distress, and ensuring honesty and transparency in data collection, analysis, and reporting.

Bayesian vs. Frequentist Statistics

• Bayesian statistics: Incorporates prior beliefs or knowledge (prior probabilities) and updates them with new evidence to calculate posterior probabilities, emphasizing uncertainty and subjective interpretations.
• Frequentist statistics: Focuses on probabilities derived from sample data alone, without incorporating prior beliefs, using p-values and confidence intervals for inference based on observed data.

Statistical Power

• Statistical power: Probability that a study will detect an effect when it exists (1 - β).
• Low power increases the risk of Type II errors (false negatives) and affects the reliability and validity of study results.

Meta-Analysis

• Meta-analysis: Statistical technique for combining results from multiple studies to obtain an overall estimate of the effect size.
• It provides a comprehensive summary of existing research, identifies patterns or inconsistencies across studies, and enhances the reliability and generalizability of findings.

Parametric and Non-Parametric Tests

• Parametric tests: Examples include Mann-Whitney U test, Wilcoxon signed-rank test, and Spearman correlation.
• Non-parametric tests: Used when parametric assumptions are not met.

Analysis of Variance (ANOVA)

• ANOVA: Compares means between three or more groups to determine if there are statistically significant differences.
• Used in psychology to analyze data from experiments with multiple treatment conditions or independent variables.

Regression Analysis

• Regression analysis: Examines the relationship between one or more independent variables (predictors) and a dependent variable (outcome).
• Examples include predicting academic performance based on study hours, or predicting happiness based on income and social support.

Effect Size Measures

• Effect size: Quantifies the strength of a relationship or the magnitude of a difference between variables.
• Examples:
  • Cohen's d: Standardized difference between two means.
  • Eta-squared (η²): Proportion of variance in the dependent variable explained by the independent variable(s).

This quiz explores the role of statistics in psychology research, including data visualization and ethics in statistical analysis and reporting.