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Table of Contents

How to arrange data in Excel (so it can be imported into SPSS) ................................. 2

1.1 General guidelines for arranging data in Excel ......................................................................... 2

1.2 Scale variables (i.e., quantitative) ............................................................................................. 2

1.3 Scale variables (i.e., quantitative) from a repeated measures design ...................................... 2

1.4 Nominal or Ordinal variables (i.e., categorical) ........................................................................ 3

1.5 Nominal or Ordinal variables from a repeated measures design ............................................. 3

Additional Resources.................................................................................................. 4

Created by ASK (2012) Page 2 of 4

How to arrange data in Excel (so it can be imported into SPSS)

In this tutorial it is assumed that you know what a variable is, can identify most of the variables in

your dataset and have identified the level of measurement for each variable. If not, please review

the relevant resources on Blackboard.

In addition, throughout this tutorial I will use the terms Scale, Nominal and Ordinal to describe

different types of data because these are the levels of measurement used in SPSS. If you are

unsure what these terms mean, please see the levels of measurement guide on Blackboard.

1.1 General guidelines for arranging data in Excel

Variables always go in columns. That means that all your variable names will be in the first row of

the dataset. Each row should represent a subject, participant or occurrence (this could be a date

or time, etc… depending on the experiment). For example, if you have a questionnaire, row 1 will

contain all responses for participant 1, row 2 for participant 2, etc…

1.2 Scale variables (i.e., quantitative)

Each scale variable is in its own column. Figure 1 shows data for 5 subjects (i.e. participants)

across 6 scale variables.

Figure 1. Quantitative measurements.

1.3 Scale variables (i.e., quantitative) from a repeated measures design

Because each repeated measure is a separate variable, each one is in its own column. Figure 2

shows data for 5 subjects for 1 measure (weight in kgs) across 3 time periods (baseline, 6 months

and 12 months). Because each participant’s weight was measured at each time period, and

because you can only enter one piece of information (i.e., one weight) in each cell for each

participant, each measurement needs its own column.

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Figure 2. Repeated measures design quantitative measurements.

1.4 Nominal or Ordinal variables (i.e., categorical)

Because each repeated measure is a separate variable, each one is in its own column. Figure 3

shows data for 5 subjects across 3 qualitative variables (Gender and Experimental Condition are

nominal and Weight group is ordinal).

Figure 3. Independent categorisations or groupings.

1.5 Nominal or Ordinal variables from a repeated measures design

Each nominal and/or ordinal variable is in its own column. Figure 4 shows data for 5 subjects for 1

measurement (weight group) across 2 time periods (baseline and post-experiment). Just as with

the repeated measures scale variables, because each participant was categorised into a particular

Weight Group at each time period, and because you can only enter one piece of information (i.e.,

one weight group) in each cell for each participant, each measurement needs its own column.

Figure 4. Repeated measurements of all subject.

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Additional Resources

In the Getting Started folder under the SPSS resources section, you may be interested in the

following:

1. How to identify variables in your dataset

2. Levels of measurement (nominal, ordinal and scale variables)

3. How to code categorical variables (check this out if you have data from a questionnaire)

* If you are unsure about which variables are categorical, have a look at the Levels of

Measurement guide mentioned above.

Return to:

1.1 General guidelines for arranging data in Excel

1.2 Scale variables (i.e., quantitative)

1.3 Scale variables (i.e., quantitative) for a repeated measures design

1.4 Nominal or ordinal variables (i.e., categorical)

1.5 Nominal or ordinal variables for a repeated measures design