Dec 08 2022 06:03 PM
My sample data has a column by Gender and another column for the corresponding Height. I inserted a new column between those two columns. I need all of the Females to be in one column and all the Males to be in another column. How do I do this?
Dec 08 2022 07:00 PM
I inserted a new column between those two columns. I need all of the Females to be in one column and all the Males to be in another column. How do I do this?
How are they identified in that one column? By the words "Female" and "Male"? Something else? The answer to the "How" depends on how you've got the genders identified now.
BUT can I also ask another question: WHY do you want to separate the genders in the first place? In a well designed database, you might well have a column that is headed "Gender," and that column contains designations like "M" and "F" [and these days it could have additional words or codes], and then you'd have other columns with such things as name, height, eye color, education--=whatever you're tracking==but there'd be no need to separate the people (or their associated characteristics) into different columns based on their gender. So what is it that makes you think that's a necessary or good idea?
Excel has wonderful data processing capabilities when working with a well-designed database. So my concern is that there needs to be a good reason to make the change you're describing.
[I ask, by the way, as a person who was the director of a major corporation's HR/Payroll database for many years before I retired; it's not a frivolous question.]
Dec 08 2022 07:08 PM
Dec 09 2022 07:14 AM
Now you're asking an altogether different set of questions, ones I can't help you with. (I've never studied statistics or statistical analysis, despite two graduate level degrees.) My only point (and the basis for my question about "Why?") was that Excel could handle whatever analyses and processing you're doing without separating males from females into separate columns. I still will hold to that position, but as to your questions on
"Standard Error", Null Hypothesis (µ=?), the "T Test Statistic", Left Tailed Test, the Critical Value and P Value
I must defer to others. Best wishes.