This is a handout that accompanies a blog post on MattKushin.com. Search "data legend." The handout is used to help teach students how to take quantitative data and enter it into a spreadsheet so that it can be analayzed using software such as SPSS.

1. Com 435: Communication Research
Shepherd University · Professor Matthew J. Kushin | MattKushin.com
Data Entry: For Quantitative Research
Comm 435: Communication Research
When you do quantitative research, you need to get your data entered onto the computer before we can analyze
it using statistical software.
Preparing the Data: Turning Answers into Numbers
The computer can only analyze numbers. If you recall several lectures ago, we said that some questions don’t have
numbers in them – we assign them numbers (i.e., nominal data). For example:
Are you a student or non-student? Student Non-student
We need to assign a number to these kinds of questions. As long as we are consistent, it doesn’t matter what # we
assign but the convention is to start at 1. So, we assign 1 to “student” and 2 to “non-student”.
Similarly, if we ask:
Which is your favorite type of ice cream? Vanilla Chocolate Strawberry Rocky Road
We can assign (1) to Vanilla, (2) to Chocolate, (3) to Strawberry, and (4) to Rocky Road
Ordinal data is a little tricky.
Rank these 4 types of ice cream from least favorite to most favorite: Vanilla, Chocolate, Strawberry, Rocky Road
We know that there are 4 possibilities. Just like nominal data, we assign #’s to each possible answer. (1)Vanilla, (2)
Chocolate, and so on. In addition, for data entry purposes we actually have to make 4 sub-variables out of this to
hold our data. The reason is, this is like asking someone 4 questions: Which ice cream would you rank lowest?
Second lowest? Third lowest? Best? See data entry on ordinal data below.
Scales are much easier because there is a # inherent to them.
On a scale of 1-5, how much do you like ice cream?
Keeping Track: Data Legend
We need to be able to associate the computer data with the questions and responses. This is VERY important, or
we won’t be able to interpret the data. So we need to create a “Data Legend”.
On a separate file or paper:
1), assign each variable a label (max 13 letters). So, “schoolstatus”, “favicecream” and “rankicecream” work.
2) If it is nominal or ordinal label it in parentheses.
3) With each label, make a list that indicates what # we have assigned to each term within our measurement, by
placing the # in parentheses.
schoolstatus(Nominal) (1) Student (2) Non-student
favicecream (1) Vanilla, (2) Chocolate, (3) Strawberry, and (4) Rocky Road
Labeling ordinal data is a little trickier. As I said, we have to create a sub-variable to each level of ranking in our
variable. So, 4 sub-variables for our example above:
Rank these 4 types of ice cream from least favorite to most favorite: Vanilla, Chocolate, Strawberry, Rocky Road
In addition to our normal practice:
rankicecream(Ordinal) (1) Vanilla, (2) Chocolate, (3) Strawberry, and (4) Rocky Road

2. Com 435: Communication Research
Shepherd University · Professor Matthew J. Kushin | MattKushin.com
We have to create 4 questions for data entry purposes, we’ll actually create 4 labels and assign a “#” to each level
of ranking. So we add:
rankicecream1 Lowest
rankicecream2 2nd
lowest
rankicecream3 3rd
lowest
rankicecream4 highest
NOTE: If we do a “check all that apply” question – we also use this data entry method.
Data Entry
Data are to be entered into a spreadsheet in MS Word Excel compatible format.
Each person’s responses (surveys) or unit of analysis (content analysis) should go on a separate row (horizontal)
and each item (variable) represented should be a separate column (vertical). Type the variable label in the first row
in every column.
As long as everyone follows the same protocol, you can enter your data in separate files and merge them into 1
file. After entering all data, merge them into 1 file. Make sure they are entered correctly.
Save your Excel file and Data Legend where you can access them in the future (like emailing it to yourself). We will
import your data into SPSS for analysis in an upcoming step.
Applying our 4 sub-label strategy above for ordinal data, our data entry would look like this. Notice we don’t
bother creating a label that just says “rankicecream” – as in this case that will just serve us to interpret the data: