Hello this is for my graduate level Biostatistics class We h

Hello, this is for my graduate level Biostatistics class. We have to write an answer that is a paragraph long. The question that I need answered is in italicsbelow. I\'m learning about binomial distribution and all of that good stuff. Thanks for your help.

Choose one of the variables described below and then identify how you decided to measure the variable. What type(s) of distribution(s) would you generate with this variable when reporting and interpreting these data? Explain your reasoning.

First, to identify the data I would look at a few possible variables to attempt to configure the data such as the individual\'s usual sleep patterns, typical exam grades, classmates scores from (0 to 100%), etc. Based off of those variables I would measure usual sleep patterns and typical exam grades under qualitative, discrete, and ordinal due to qualitative data means having to do with quality/qualities and is capable of being measured. Discrete variables are those with a set value, and ordinal scales which it\'s values convey in order or rank. Under the, \"Classmates scores\" variable I would describe this under Continuous, Quantitative, and Ratio. This variable is measured under Continuous because these variables are measured along any place beyond the decimal point, Quantitative research methods because you want to know how many times or how often something happens (numerical data), and a ratio measure scale indicates that a set of values has a true zero.

Solution

Here the variable Individual usual sleeping pattern varible is an ordinal variable, primarly this was classifed as REM ( Rapid eye moment) NERM ( non rapid eye moment) again the NERM classified as stages 2,3 and 4 . The measurement of the variable in each stage is the number of minutes/hours spent on respective type/stage. The number of hours/mins spent is a continous type and the distribution of sleeping time follows normal distribution.

The variable classmate score is a continous type which follows normal distribution.