Question 1119322: imagine if our data that is originally collected is categorical in nature. In other words participants are not asked to give an answer on a scale but rather to select a category. One disadvantage to this method of collecting data is that researchers cannot change categorical data to data measured on a scale. Think about categories of age (e.g. 10-20, 21-30, etc.). Imagine that researchers decided that they did in fact want to conduct a t-test. Well now they needed their age scores on a scale. They cannot take all the participants in the 10-20 category and ascertain whether they are 10, 11, etc. However, if data is originally collected on a continuous scale (e.g. the actual age is recorded rather than the category) then researchers can always convert it to categories if needed.
Let's assume though that researchers did collect the data in a categorical fashion. In fact, in my example researchers are going to perform a 2 x 3 chi-square analysis to determine if there is a relationship between eye color (blue or brown) and political affiliation (Republican, Democrat, or other). We learned this week that when we use a chi-square analysis that the responses need to be exhaustive? What does this mean?
Answer by stanbon(75887)   (Show Source):
You can put this solution on YOUR website! We learned this week that when we use a chi-square analysis that the responses need to be exhaustive? What does this mean?
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The row/column categories must cover all the possible response data.
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Cheers,
Stan H.
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