This tool allows you to perform various types of analyses, depending on whether your data has sub-variables or unique variables. Please review the explanations below to understand which analyses apply to your data.
Cronbach’s Alpha is used to assess the reliability or internal consistency of grouped sub-variables. It checks whether multiple variables that are meant to measure the same concept are, in fact, doing so consistently.
Item-Total Statistics show how each sub-variable contributes to the overall reliability of a scale. It provides insights into how Cronbach's Alpha changes if an item is removed, and whether removing an item improves the reliability.
Pearson Correlation Matrix shows the strength and direction of relationships between variables. A correlation coefficient ranges from -1 to 1. A value of 1 means a perfect positive relationship, 0 means no relationship, and -1 means a perfect negative relationship.
OLS Regression is used to test hypotheses and understand how one dependent variable is influenced by several independent variables.