Both numeric and nominal data in one questionnaire

My questionnaire has both numeric and nominal data. Which SPSS test will show that the variables are related?

1 comment to Both numeric and nominal data in one questionnaire

  • Afroze

    Both the terms you mentioned are very important for SPSS research. The features of nominal scale are given below.

    1. Nominal scale is organized by an attribute.

    2. This scale can be a member of a group or cannot be.

    3. The number of observations is being counted with or without an attribute which is fit the category is one of the characters of nominal scale.

    4. Percentages or proportions are used in this scale.

    5. This scale is represented either by frequencies or by category instead of raw numbers by category.

    6. Most of the time, this scale is displayed in contingency tables. However, dividing up into numbers which meet each selected criteria is one of the character of this table.

    Numerical scale is mainly characterized by a number or quantitative in SPSS research. The main features of numerical scale are given below.

    A. Interval or continuous character

    1. A number which varies in some continuous way is one of the features of this numerical scale.

    B. Discrete

    1. Integer number values are the main character of this scale.

    2. This can be used for describing a continuous scale

    Scatter plot can be good way to visualize the two data sets is related with each other or not. This kind of graph put one variable’s value on another. A scatter plot can tell us several things weather it seems to be a relationship between variables or not, what kind of relationship it is and whether any cases are markedly difference with others. For making a scatter plot in SPSS research, you have to click in graph option then interactive and then scatter plot option. After that you need to put the variables name. Moreover, you can adjust the color, size and style of each plot. In general, if you find a roughly circle shape in your figure that means the two variables are not related with each other. And for other form like linear or triangle, there is some association between two variables. Furthermore to know how much these variables are related you have to go for some statistical test or for SPSS research. If you have can arrange you nominal data as an order you can do Spearman Rank correlation. Otherwise you can do Kendall’s a or b. Both of this option you can find from correlation option from analyze menu.

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