# SPSS Basic Skills Tutorial: Data Entry

When we are creating a new data set, it is typical to start by definining the names and other properties of the variables first and then entering the specific values into each variable for each independent source of data. Recall that there is one row for each independent source of data and one column for each characteristic (i.e., variable) that we have measured from each data source. There are times, however, when we decide to add additional variables after we have entered some of the data. Adding variables after the fact does not present any special challenges; we simply go to the variable view, click in an empty row, and start defining our new variables as we do below. The first step to defining variable names and properties is to select the variable view tab in the data window. Then we can create (or edit) each of the properties below.
• #### Name

The name of each SPSS variable in a given file must be unique; it must start with a letter; it may have up to 8 characters (including letters, numbers, and the underscore _ (note that certain key words are reversed and may not be used as variable names, e.g., "compute", "sum", and so forth). To change an existing name, click in the cell containing the name, highlight the part you want to change, and type in the replacement. To create a new variable name, click in the first empty row under the name column and type a new (unique) variable name.

Notice that we can use "cat_dog" but not "cat-dog" and not "cat dog". The hyphen gets interpreted as subtraction (cat minus dog) by SPSS, and the space confuses SPSS as to how many variables are being named.

• #### Type

The two basic types of variables that you will use are numeric and string. Numeric variables may only have numbers assigned. String variables may contain letters or numbers, but even if a string variable happens to contain only numbers, numeric operations on that variable will not be allowed (e.g., finding the mean, variance, standard deviation, etc...). To change a variable type, click in that cell on the grey box with ...

Clicking on this box will bring up the variable type menu:

If you select a numeric variable, you can then click in the width box or the decimal box to change the default values of 8 characters reserved to displaying numbers with 2 decimal places. For whole numbers, you can drop the decimals down to 0.

If you select a string variable, you can tell SPSS how much "room" to leave in memory for each value, indicating the number of characters to be allowed for data entry in this string variable.

• #### Width

The width of a variable is the number of characters SPSS will allow to be entered for the variable. If it is a numerical value with decimals, this total width has to include a spot for each decimal, as well as one for the decimal point. You can change a width by clicking in the width cell for the desired variable and typing a new number or you can use the arrow keys at the edge of the cell

• #### Decimals

The decimals of a variable is the number of decimal places that SPSS will display. If more decimals have been entered (or computed by SPSS), the additional information will be retained internally but not displayed on screen. For whole numbers, you would reduce the number of decimals to zero. You can change the number of decimal places by clicking int he decimals cell for the desired variable and typing a new number or you can use the arrow keys at the edge of the cell

• #### Label

The label of a variable is a string of text to indentify in more detail what a variable represents. Unlike the name, the label is limited to 255 characters and may contain spaces and punctuation. For instance, if there is a variable for each question on a questionnaire, you would type the question as the variable label. To change or edit a variable label, simply click anywhere within the cell.

• #### Values

Although the variable label goes a long way to explaining what the variable represents, for categorical data (discrete data of both nominal and ordinal levels of measurement), we often need to know which numbers represent which categories. To indicate how these numbers are assigned, one can add labels to specific values by clicking on the ... box in the values cell

Clicking here opens up the Value Labels dialogue box.

• Click in the Value field to type a specific numeric value
• Click in the Label field to type the corresponding label
• Click on the Add button to add this pair of value and label to the list
You can remove a pairing created above by clicking on that pair and then clicking on the delete button. Similarly, you can change pairing by clicking on the pair, then typing in a new value, a new label, or both; then, you click on the Change button. When you are satisfied with the definitions of each value, click on the OK button

The real beauty of value labels can be seen in the Data View by clicking on the "toe tag" icon in the tool bar , which switches between the numeric values and their labels

• #### Missing

We sometimes want to signal to SPSS that data should be treated as missing, even though there is some other numerical code recorded instead of the data actually being missing (in which case SPSS displays a single period -- this is also called SYSTEM MISSING data). In this example, after clicking on the ... button in the Missing cell, I declared "9", "99", and "999" all to be treated by SPSS as missing (i.e., these values will be ignored)

• #### Columns

The columns property tells SPSS how wide the column should be for each variable. Don't confuse this one with width, which indicates how many digits of the number will be displayed. The column size indicates how much space is allocated rather than the degree to which it is filled.

• #### Align

The alignment property indicates whether the information in the Data View should be left-justified, right-justified, or centered

• #### Measure

The Measure property indicates the level of measurement. Since SPSS does not differentiate between interval and ratio levels of measurement, both of these quantitative variable types are lumped together as "scale". Nominal and ordinal levels of measurement, however, are differentiated

### Entering the Data

The first step for entering the actual data is to click on the Data View tab.

To enter new data, click in an empty cell in the first empty row. The "Tab" key will enter the value and jump to the next cell to the right. You may also use the Up, Down, Left, and Right arrow keys to enter values and move to another cell for data input.

To edit existing data points (i.e., the change a specific data value), click in the cell, type in the new value, and press the Tab, Enter, Up, Down, Right, or Left arrow keys.

### Lab Activities

1. Open a new data set in SPSS
2. Create a nominal variable called cat_dog that has a width of 3 with 0 decimal places. The label should be "Do you like cats or dogs better?". The values should be 1 for cats and 2 for dogs (or vice versa). Do not worry about missing data codes.
3. Create a scale variable called neatness that has a width of 8 with 3 decimal places. The label should be "Eric Cartman's Neatness Scale (higher = neater)". There will be no value labels.
4. Enter data for the following cases
• case 1 prefers cats and has a neatness of 4
• case 2 prefers dogs and has a neatness of 3
• case 3 prefers dogs and has a neatness of 7
• case 4 prefers dogs and has a neatness of 2
• case 5 prefers cats and has a neatness of 5
• case 6 prefers cats and has a neatness of 1
• case 7 prefers cats and has a neatness of 3
• case 8 prefers dogs and has a neatness of 6
5. Change the neatness of the second case from 3 to 6, like you would if you discovered a data entry error.