As an example, if you want to see if there is a relation between personality and affection you can use a correlation analysis. Personality is a concept that, according to some authors, comprises 5 dimensions: extroversion, kindness, conscientiousness, neuroticism and openness to experience. As for affection, some authors refered 2 dimensions: positive and negative.
Using the commands as shown in the following image, a new window will open (second image) where you can select the personality and affection variables .
The output will show all the correlations between variables. The ones marked with ** are correlations significant at the 0.01 level and the ones marked with * are significant at 0.05 level.
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1. Age: _________2. Gender:
3. Marriage status:
4. Educational background:
5. Family income (month):
The previous questions in a survey, which are used to describe the sample of a study, are called sociodemographic variables. This variables will assume the following types and measures in SPSS.
Question 
Type 
SPSS 



Type 
Measure 
Age 
Quantitative 
Numeric 
Scale 
Gender 
Qualitative 
Numeric 
Nominal 
Marital status 
Qualitative 
Numeric 
Nominal 
Educational background 
Qualitative 
Numeric 
Ordinal 
Family income (month) 
Qualitative 
Numeric 
Ordinal 
Variables can be qualitative or quantitative:
An example of a nominal variable is gender: either you are male or female (the categories are mutually exclusive) and one of the categories comprehensively qualifies the individual. Numbers may be used to identify the categories of a measure. For this reason the variable takes a numeric type (Type = numeric): “0” for male and “1” for female. As for marital status, categories can have the following values: “1” = single; “2” = married; “3” = divorced; “4” = widower. The use of numbers is an easier way to enter data in SPSS, saving time and effort.
For ordinal variables, besides being mutually exclusive and exhaustive , they show an order of magnitude. The variable educational background is a good example, with 4 categories. It can assume the following values: “1” = Elementary school; “2” = Middle School; “3” = High school; “4” = professional course; “5” = College. We know that an individual on category 2 presents a higher order than other category 1. This does not mean, however, that the value 2 is twice the value of 1; nor does it mean that the difference between categories 2 and 3 is the same as the difference between categories 1 and 2.
An example of an interval variable is temperature in Celsius. A difference of five values is equal at any point of the scale, either between 16 and 21, or between 36 and 41. Although a zero value can exist , this does not mean the absence of heat and, as such, is not an absolute zero. In temperature, zero is an arbitrary value corresponding to the freezing point of water.
Ratio variables have an absolute zero, in addition to all the properties of an interval variable. This is true for income, where a zero corresponds to an absence of income.
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]]>In addition to the use of SPSS, we also provide tips on how to build questionnaires, which statistics should be used in every case, and more.
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