Advanced Research Methods in Psychology

These flashcards focus on key terms and concepts related to regression analysis in psychology.

Coefficient of Determination (R²)

A measure that explains the proportion of variance in the dependent variable that can be explained by the independent variable(s).

p-value

The probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Statistical Significance

A determination of whether an observed effect in data is likely due to chance or represents a true association.

Correlation between two variables (X and Y)

A strong negative correlation (e.g., r = -0.80) indicates that as one variable increases, the other variable tends to decrease significantly.

Social Class & Visual Attention

Research suggests that individuals from lower social classes may spend more time looking at other people compared to those from higher social classes.

Research hypotheses

H1: There is a negative correlation (ρ < 0) between social class and looking time. H0: There is no correlation (ρ = 0).

Regression analysis

Regression analysis reveals specific relationships, indicating that self-categorization into a higher social class is associated with shorter social gazes (b = -0.113, 95% CI = [-0.205, -0.020]).

Interpretation of intercept in regression

In a regression equation, the intercept represents the predicted value of Y when X is zero; however, it may not always provide meaningful information.

Significance in regression

To assess the significance of results, we test if the correlation and slope coefficients are significantly different from zero, indicating a reliable relationship.

Standard Error of Estimate

The standard error of estimate quantifies the average distance that predicted values deviate from actual values in regression analysis.

Measuring error in regression

Residuals represent the difference between observed and predicted values, and understanding their distribution is crucial for assessing model accuracy.

Causation vs. correlation

It is important to remember that correlation does not imply causation; other variables may affect the relationship observed.

Predictive regression equation example

Using the regression equation y = 1.76x + 14, if expectations increase, we can predict a corresponding increase in performance scores.

What is correlation