Irfan Ahmed, PhD

Factor analysis is a collection of methods used to examine how underlying constructs influence the responses on a number of measured variables. There are basically two types of factor analysis: exploratory and confirmatory. Exploratory factor analysis (EFA) attempts to discover the nature of the constructs influencing a set of responses. Confirmatory factor analysis (CFA) tests whether a specified set of constructs is influencing responses in a predicted way. SPSS only has the capability to perform EFA. CFAs require a program with the ability to perform structural equation modeling, such as LISREL or AMOS. The primary objectives of an EFA are to determine the number of factors influencing a set of measures and the strength of the relationship between each factor and each observed measure. To perform an EFA, you first identify a set of variables that you want to analyze. SPSS will then examine the correlation matrix between those variables to identify those that tend to vary togeth...

Pearson correlation A Pearson correlation measures the strength of the linear relationship between two continuous variables. A linear relationship is one that can be captured by drawing a straight line on a scatterplot between the two variables of interest. The value of the correlation provides information both about the nature and the strength of the relationship. • Correlations range between -1.0 and 1.0. • The sign of the correlation describes the direction of the relationship. A positive sign indicates that as one variable gets larger the other also tends to get larger, while a negative sign indicates that as one variable gets larger the other tends to get smaller. • The magnitude of the correlation describes the strength of the relationship. The further that a correlation is from zero, the stronger the relationship is between the two variables. A zero correlation would indicate that the two variables aren’t related to each other at all. Correlations only measure the strength...

DESCRIPTIVE STATISTICS Analyses often begin by examining basic descriptive-level information about data. The most common and useful descriptive statistics are Mean Median Mode Frequency Quartiles Sum Variance Standard deviation Minimum/Maximum Range Note: All of these are appropriate for continuous variables, and frequency and mode are also appropriate for categorical variables. If you just want to obtain the mean and standard deviation for a set of variables Choose Analyze   then goto Descriptive Statistics then goto Descriptives. Move the variables of interest to the Variable(s) box. Click the OK button. If you want to obtain any other statistics Choose Analyze then goto Descriptive Statistics then goto Frequencies. Move the variables of interest to the Variable(s) box Click the Statistics button. Check the boxes next to the statistics you want. Click the Continue button. Click the OK button.