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SPSS Skill: Qualitative vs. Quantitative Research using SPSS SPSS SKILL Animation https://youtu.be/HtWvHcKMPfA This Video Learning explains textbook classification and SPSS classification of Quantitative data and Qualitative data. It clarifies that Quantitative data is also Continuous data and Qualitative data in SPSS is know as Categorical data. SCALE measure in SPSS are used to set up Quantitative variables: In SPSS, your Quantitative data is entered through creating variables with have SCALE measure and Categorical data of your research is dealt by creating variables that have ORDINAL and NOMINAL measures. When you have data that is being measured on a standard metric scale, then it is good idea to use SCALE measurement for the variable in SPSS. For example, age, marks secured, height, weight, income etc are examples of Quantitative VARIABLE measured on SCALE measure. ORDINAL and NOMINAL measures in SPSS are used to set up Qualitative variables: Further is worth understanding that SCALE data can be measured in Interval Scale or a Ratio Scale. RATIO SCALE measure of Quantitative variables: A ratio scale has a true zero point in the measurement. For Example, Dividend paid on stock of a company say ABC Limited is $40 per share and that of XYZ is $30 per share. Here We are using Ratio scale of measurement as we can clearly not only tell that $40 is more that $30 and there is difference of $10 but there is also a true zero point as zero dividend means no dividend. So in Ratio Scale zero value makes sense and it represents absence of that particular phenomenon, for example zero dividend means absence of dividend or no dividends. So, there is a true zero in Ratio Scale. INTERVAL SCALE measure of Quantitative variables: In Interval Scale there is no true zero. Temperature in Fahrenheit and Celsius is a good example of interval scale because zero-degree temperature in Fahrenheit or Celsius does not mean absence of temperature. ORDINAL measure for Qualitative variables/Categorical Data: Ordinal Measure in SPSS represents categories that are ranked. For example, if there is a questionnaire has a question as to how satisfied you are from your job and there are categories like 1-very dissatisfied, 2-dissatisfied, 3-satisfied and 4-very satisfied the this is of course categorical data that can be represented through ORDINAL MEASURE in SPSS. But distance between categories like 1-high,2medium ,3-low can not be calculated for ORDINAL data. NOMINAL measure for Qualitative variables/Categorical Data:
Nominal Measure in SPSS is used to set up categorical and Qualitative data. There are of course categories like 1-Sales, 2-Accounting, 3- Research etc. but these categories are not ranked, and we are not saying 3 (Research) is better than 2(Accounting). Similarly, we are not saying that 2 is better than 1 or Accounting is better than Sales. So, with Nominal measure data is categorized but not ranked. Moreover, variables like gender, 1-male 0-female can also be measured on Nominal Measures. Similarly, Religious affiliations and data about various geographical zone can also be measured on Nominal Scale. Similarly, marital status like 1-never married, 2-separated, 3-divorced,4-single etc can also be set on Nominal Measure. With this understanding, you should set up your research variables accordingly in SPSS so that statistical analysis can be performed accordingly.
SPSS Skill: Know Your Data Know Your SPSS Data: Skill Animation https://youtu.be/-SRMvWo4iNw
SPSS stands for Statistical Package for Social Sciences. SPSS is a powerful Statistical data analysis program as compared to other Programs designed for this purpose. This Video Learning provides you with the skill to understand SPSS sheet that has two views, Variable View and Data View. The learning shows how to define a numeric variable namely age. Further, it shows how to set up width of the n