Let’s start with an example
I’m going to use this example to help you understand how to enter the data. Suppose you want to find out if there is a relationship between the amount of water consumed (in glasses) and skin elasticity ratings (1-10 with 10 being the best). You select 5 participants. Each participant is given a different about of water and each is asked to rate their skin elasticity. Here are the data. You can see the how many glasses of water each participant drank and their personal ratings of their skin elasticity.
What you want to know
You want to know if there is a relationship between the amount of water that someone drinks and their personal rating of skin elasticity. Do people think there skin elasticity is better when they drink more or less water? How strong is the relationship between these two variables, amount of water and skin elasticity rating? Why not just look at the data?
Just looking at the data, you can probably see that there is a relationship between the two variables. You can probably see that as the amount of water consumed increases, the rating of skin elasticity also increases. So, it appears that there is a relationship between the variables and a relatively strong and predictable on at that. However, sometimes you will analyze data from more than five participants. At a guess, most times you will have many more data points than what you see in this example. When this is the case, it becomes more difficult to just eyeball it. The Pearson’s r and the scatterplots can help us see relationships between variables in a numeric and graphic way. This can be helpful when our data sets are large.
You will use the two columns of your SPSS data file to enter the data. These columns will contain the data collected in your experiment.
What goes in each column?
Enter the data collected in the first variable of in column 1. Enter the data collected in for the second variable in column 2. In our example experiment, the first variable was amount of water consumed by each participant. So, we enter all the data collected for this variable into the first column.
See the number 1 in the first cell of the first column? That indicates that the first participant consumed 1 glass of water. In our experiment, the second variable was rating of skin elasticity. So, we enter all the data collected for this variable into the second column. See the number 1 in the first cell of the second column? That indicates that the first participant rated themselves as having a number 1 for skin elasticity.
Name the columns
When you are finished entering the data, double click on the top of each column to name it. The Define Variable box will pop up and you can enter a new name for each variable in the Variable Name area. Give each variable a meaningful name. Click OK when you are finished using the Define Variable box and it will disappear.
Meaningful Names
I decided to name my first column “water.” I decided on this name because this column has data on the amount of water each participant consumed. I decided to name my second column “skin” because it contains data on each participant’s skin elasticity rating.
Save the data!
Always remember to save your data file to a meaningful place with a meaningful name. You don’t want to lose this file and enter the data all over again. I decided to name my data file “Correlation between glasses of water and skin elasticity data.sav.” It’s a long name but this file will be very easy for me to identify in the future.
Background | Enter Data | Analyze Data | Interpret Data | Report Data
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