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Summary Wk2.docx Case Study: MBA Schools in Asia-Pacific QNT 561 University of Phoenix The data in the data set that was presented to us is diverse and comprehensive and aids in determining the trends, fee structures and percentage of foreign students in th $5.49   Add to cart

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Summary Wk2.docx Case Study: MBA Schools in Asia-Pacific QNT 561 University of Phoenix The data in the data set that was presented to us is diverse and comprehensive and aids in determining the trends, fee structures and percentage of foreign students in th

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W Case Study: MBA Schools in Asia-Pacific QNT 561 University of Phoenix The data in the data set that was presented to us is diverse and comprehensive and aids in determining the trends, fee structures and percentage of foreign students in the listed Asian Pacific Universities. There are sever...

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  • January 12, 2021
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Case Study: MBA Schools in Asia-Pacific

QNT 561

University of Phoenix




The data in the data set that was presented to us is diverse and comprehensive and aids in

determining the trends, fee structures and percentage of foreign students in the listed Asian

Pacific Universities. There are several tables and graphs below that aid the deciphering of the

information provided to us in the data set.

Quantitative/Qualitative Data

, The data collected from the data set that was provided was in large part quantitative data.

Quantitative data is data that can be measured and is expressed as numbers. This data is always

clear and specific and is accurate when reliably analyzed. In the data set there was also some data

that was qualitative data. This type of data is data that approximates or characterizes. Unlike the

quantitative data type this data type is non-numeric in nature. As shown in the attached table we

can see a breakdown of the data. We see that there are several categories of data that are

qualitative data. The data in these columns is primarily a yes or no question which indicates that

the data is in fact qualitative because it is non-numerical in nature. In addition to having

quantitative and qualitative data the quantitative data can be broken down further into discrete or

continuous. Discrete data is data that is that can be categorized into a classification and is based

on counts. Discrete data has a finite number of values and cannot be subdivided equally. On the

other side of the spectrum is continuous data. Continuous data that can take any value and can be

meaningfully subdivided. An example of continuous data would be a person weight in that the

number can be any numerical value in the range to include the hundredths and thousands of a

pound.




Quantitative Variables Data

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