Pearson r correlation in spss how to calculate and interpret part 1. Pearson s correlation coefficient, r, is sensitive to outliers, which can have a very large effect on the line of best fit and the pearson correlation coefficient. Pearson s r correlation is used to assess the relationship between two continuous variables. You can find the pearson s r statistic in the top of each box. Correlation in ibm spss statistics discovering statistics. The slope is given in the b column to the right of the name of the x variable. Please read the article at and pay special attention to how. Pearsons productmoment correlation using spss statistics. We will learn how to conduct a simple correlation in spss, how to interpret it, and how to. In these boxes, you will see a value for pearson s r, a sig. Pdf test for significance of pearsons correlation coefficient. The more time that people spend doing the test, the better theyre likely to do, but the effect is very small. Pearsons product moment correlation coefficient, or pearson s r was developed by karl pearson 1948 from a related idea introduced by sir francis galton in the late 1800s.
Before running a pearson s r, be sure to check for the normality of the two continuous variables using skewness and kurtosis statistics. Outliers can grossly inflate or deflate a pearson r correlation. This is my teaching slides for undergraduate spss class on pearson correlation. Pearson correlation spss tutorials libguides at kent state. In this manual we will rely on the example data gathered from a fictional educational survey. I demonstrate how to perform and interpret a pearson correlation in spss. A scatter plot and correlation analysis of the data indicates that there is a very strong correlation between reading ability and foot length r.
By extension, the pearson correlation evaluates whether there is statistical evidence for a linear relationship among the same pairs of variables in the population, represented by a population correlation. Pearson correlation coefficient and interpretation in spss. The first correlation coefficient that we will look at is the pearson correlation coefficient. Computing a pearson correlation in spss is a simple procedure. These values range from 0 to 1 for positive correlations and 1 to 0 for negative correlations. The default setting is pearsons productmoment correlation, but you can also calculate. Interpreting spss correlation output correlations estimate the strength of the linear relationship between two and only two variables. For the haemoglobinpcv data, spss produces the following correlation output. Pearson correlation this is the person correlation coefficient r value. The model summary table reports the same value for pearson r obtained with the. Although i made the slides, the content is still ed to the rightful owners.
Therefore, in some cases, including outliers in your analysis can lead to misleading results. The purpose of this lecture is to illustrate the how to create spss output for correlation and. The pearson s r for the correlation between the water and skin variables in our example is 0. The larger the number, the stronger the linear association between the two variables i. Therefore, it is best if there are no outliers or they are kept to a minimum. Between two quantitative variables measured on same person 1 if you have a relationship p pearson correlation produces a sample correlation coefficient, r, which measures the strength and direction of linear relationships between pairs of continuous variables. Pearson s r should not be run on data that has outliers. Spss also gives the standardized slope aka, which for a bivariate regression is identical to the pearson r. However, if we consider taking into account the childrens age, we can see that. To run a bivariate pearson correlation in spss, click analyze correlate. We want to test whether any correlation we observe in the scatterplot is. How do i interpret data in spss for pearsons r and.