Data View

Click the Data View first.

Figure 2: <Figure 2>

Data can be manually entered into the Data Editor (that you see in <Figure 2>), which may be useful for entering a small dataset or making a minor edit to a larger dataset.

To be familiarised with Data Editor, let’s manually enter a sub-sample of 30 respondents from the 2009 AuSSA (Australian Survey of Social Attitudes) using <table 1>. This table includes four variables: gender, age, political orientation and social class.

Note that <Table 1> does not have a variable of identification numbers –a unique number for each respondent– which is frequently used for identifying respondents. We will create a variable of identification numbers just like what professional researchers do.

The questionnaires used for this dataset are:

Do you remember that survey data are number-based data. If you look at <Table 1>, you will see text information in the variable of gender, political orientation, and social class. Instead of providing text information to SPSS, we will enter numeric values that correspond to text information in the Data Editor. Thus, your final data will look like <Table 2>. The next section will provide more details. Thus, DO NOT start entering data in <Table 2> at this time. Please see Variable View and How to enter data in the below. It will tell you how to enter data.

Variable View

Click the Variable View at the bottom. In this spreadsheet, you need to provide information on variables in the dataset. <Table 1> has four variables, and we will add a variable of identification number (named id). Thus, we will input information on five variables: id, gender, age, political orientation and social class.

Figure 3: <Figure 3>

Let’s start entering the name of variables. The name of the variable is used to refer to that variable when you analyse data. Thus, a short variable name would make your data analysis easier. Also, variable names must be unique in the dataset. The same name can’t be assigned to more than one variable. White spaces are not allowed for variable names. Instead, you can use an “underscore(_)” or “period(.)”.

• In the first row of the first column, type id, which is the variable name of identification numbers.
• In the second row, type gender, which is the variable name of gender.
• In the third row, type age, which is the variable name of age.
• In the fourth row, type polorient, which is the variable name of political orientation.
• In the fifth row, type class, which is the variable name of social class.

Figure 4: <Figure 4>

Next, Click the Data View again to enter the value of variables. You will see the variable names you just typed at the top of the spreadsheet.

Entering id variable (Nominal variable)

id variable is used to identify respondents. Since we have 30 respondents, let’s make id variable for all 30 respondents.

1. Enter the value of id in the first row for the column of id. The value is 1 for this cell. In the next row, the value is 2, and so on…

Figure 5: <Figure 5>

2. After finishing entering 30 for the 30th respondent, we need to define the characteristics of this variable. Click the Variable View again.

3. In the Variable View, click the first row of the Decimals column (which is for id variable). The default value is 2, which indicate two decimal places. We change this into 0 (no decimal) because id is just a nominal variable.

Figure 6: <Figure 6>

4. Add a short description of id variable in the Label column. I describe it as “Identification number”.

Figure 7: <Figure 7>

5. SPSS allows three levels of measurement: 1) Nominal, 2) Ordinal, and 3) Scale (which is the same as continuous). Levels of measurement determine the types of statistical methods or graphs. So, assigning appropriate levels of measurement is important in your future analysis. Since id is a nominal variable, we will define id as Nominal. Just click the Measure column for id and change it from Unknown to Nominal.

Figure 8: <Figure 8>

6. Go back to the Data View, and check how id variable has been changed (i.e. no decimal).

Entering gender variable (Nominal variable)

gender variable has two categories: Male and Female. For convenience, we assign numerical values to each category.

• 1 = Male
• 2 = Female

1. In the Data Editor, enter numerical values that correspond to each gender category in the column of gender.

Figure 9: <Figure 9>

2. Set the variable characteristics of gender in Variable View. It should defined as ‘no decimal’, a proper label, and a correct level of measurement.

Figure 10: <Figure 10>

3. Then, we are going to assign two categories (Male and Female) to each numerical value. Click the blue shaded square for gender variable in the column of Values.

Figure 11: <Figure 11>

4. You will see the dialogue box of Value Labels. In the box, 1) type 1 in Value, 2) type Male in Label, and 3) Click Add. This means that 1 means a male respondent.

Figure 12: <Figure 12>

5. In the same manner, 1) type 2 in Value, 2) type Female in Label, and 3) Click Add. This means that 2 means a female respondent. Then, your dialogue box should look like <Figure 13>.

Figure 13: <Figure 13>

6. Close the dialogue box by clicking OK.

7. You will be back to the Data View. Do you see that your gender variable now have texts instead of numbers? If not, go to the View at the top menu and tick Value Labels (See <Figure 15>). Enabling the option of value Labels will set SPSS to display value labels instead of numerical values in the Data View.

Figure 14: <Figure 14>

Figure 15: <Figure 15>

Entering age variable (continuous variable)

1. In the Data View, enter the value of age as in the <Table 1>.

Figure 16: <Figure 16>

2. In the Variable View, set the Decimals to 0, type Age in the Label column and change the Measure into Scale (which is a continuous variable).

Figure 17: <Figure 17>

Entering political orientation variable (ordinal variable)

polorient is an ordinal variable with five categories: 1 = Far left, 2 = Left, 3 = Central, 4 = Right, 5 = Far right.

1. In the Data View, enter numerical values corresponding to each category of polorient.

Figure 18: <Figure 18>

2. In the Variable View, change the Decimals into 0, the Measure into Ordinal. And type “Political Orientation” in the Label.

Figure 19: <Figure 19>

3. Next, we will assign the categories (value labels) to the numerical values. As we did for gender, click the blue shaded square in the column of Value for polorient variable. Then, type 1 in Value and Far left in Label. And click Add. In the same way, assign the other four categories to the remaining values. Then you will see the dialogue box as in <Figure 20>. And click OK.

Figure 20: <Figure 20>

Entering social class variable (ordinal variable)

class is is an ordinal variable with six categories: 1 = Lower class, 2 = Working class, 3 = Lower middle class, 4 = Middle class, 5 = Upper middle class, 6 = Upper class.

Enter the value of class variable. The process will be very similar as what you did for enterting polorient variable. After entering social class variable, the final data should look like <Figure 21>

Figure 21: <Figure 21>