(A) Give your own example of an nominal, ordinal, interval and ratio variables.
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(A) Give your own example of an nominal, ordinal, interval and ratio variables. Explain why they are nominal, ordinal, interval, and why they are ratio. See Ms. Powell's Notes on Measurement or the link below http://www.socialresearchmethods.net/kb/measlevl.php (B) Give your own example of a continuous and discrete variable. Explain the difference between your continuous and discrete variable. (C) Describe a study that you have recently read or heard about (include a reference to the study). Answer the following: Was the study an experiment or observational study? What conclusions were drawn based on the data that was gathered (explanatory variable, response variable)? How did those conducting the study attempt to reduce bias?Explanation / Answer
(A) THis variables is known as level of measurement. In statistics, data is a important to making better conclusion. Which type of data is used for our result. There is four types of classification of data. Each type have its own properties and assumptions.
Nominal- number of males or females
A nominal level of measurement is simply a matter of distinguishing by name. It refers to quality more than quantity. The binary category of 0 and 1 used for computers is a nominal level of measurement.
Ordinary - Greade system in class study 1 to 10.
Ordinal variables can be ordered, or ranked in logical order, but the interval between levels of the variables are not necessarily known. Subjective measurements are often ordinal variables.
Interval - age specific fertility rate for 5 years group 15-19, 20-24,...
Interval data provide information about order and posses equal interval
Ratio - student present in the class out of total student
It is an interval scale with the additional property that its zero position indicates the absence of the quantity being measured.
(B) Discrete variables whose values are necessarily whole numbers or other discrete values, such as population or counts of items. Continuous variables can take on any value within an interval, and so can be expressed as decimals. For example, in theory a weight could be measured as 1 kg, 1.01 kg, or 1.009 kg, and so on. They are often measured quantities.
(C)
https://imai.princeton.edu/research/files/mediationP.pdf
Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies
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