statistics

t-test

A statistical test used to determine if there is a significant difference between the means of two groups, commonly applied in social work research to evaluate the effectiveness of interventions. It compares the means of two samples to assess whether their population means are significantly different.

ANOVA (Analysis of Variance)

A statistical method used to compare the means of three or more groups to determine if at least one group mean is different from the others. Comparing satisfaction levels across different treatment centers.

Chi-Square Test

A statistical test used to determine if there is a significant association between categorical variables by comparing observed and expected frequencies. It's often applied in surveys and studies to assess relationships between groups. relationships between categorical variables. Is there a relationship between housing status (homeless/housed) and substance use?It evaluates whether the distribution of categorical data differs from what would be expected under the null hypothesis.

null hypothesis

A statement that there is no effect or no difference, suggesting that any observed differences in data are due to sampling variability. It serves as the default position in statistical hypothesis testing. The null hypothesis is a statement that assumes any observed differences or relationships are due to chance.In hypothesis testing, the null hypothesis posits that any observed effect or difference is not caused by the variables being tested but rather by random chance.

Correlation (Pearson’s r or Spearman’s rho)

Measures strength and direction of relationships between two variables.

• Example: Is there a correlation between self-esteem and social support? Correlation coefficients indicate how closely related the variables are, with values ranging from -1 to 1.

Regression Analysis

Predicts the value of a variable based on the value of another.

• Example: Can we predict relapse based on stress and family involvement?It is a statistical method used to understand the relationship between dependent and independent variables, allowing for predictions based on one or more predictor variables.

Qualitative Analysis (non-statistical)

Used in interviews, case studies, focus groups.

• Thematic analysis, coding, and content analysis are common.Focuses on understanding patterns and themes within qualitative data, rather than quantifying. It often involves subjective interpretation of text or visual data.

Y dependent variable, X independent variable

In regression analysis, the Y variable is the outcome or response being predicted, while the X variable is the predictor or explanatory variable used to make predictions.

How does stress level affect the likelihood of relapse?

The Y dependent variable represents the predicted outcome in a regression model, while the X independent variable is the factor that impacts that outcome.

Does increased social support predict better mental health outcomes?