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.
Glasses of Water
Skin Elasticity Rating
Participant 1, Sarah
Participant 2, Juan
Participant 3, Yvett
Participant 4, Lenny
Participant 5, Burton
Rating of 1
Rating of 4
Rating of 6
Rating of 7
Rating of 9
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?
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.
Two columns of data
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.
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.
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.
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
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.
Enter Data |
Analyze Data |
Interpret Data |