Hi There,
I would like to know more about transforming data. I know that for parametric statistics data needs to be normally distributed, but I am confused about when this does and does not apply.
Doesn't transforming data to make it normally distributed hide any experimental effects you have?
I have ran an experiment which should have resulted in differences in responding to questionnaire items. My hypothesis predicts a certain pattern of responding (e.g. higher ratings vs lower ratings) on a set of items for participants in different conditions. If I normalise the data to get rid of any skew towards lower or higher ratings, am I just going to hide any experimental effects? E.g. if group one averages a score of 7 out of 10 on an item while group two averages a score of 3/10 and then I normalise it so they both have similar means.
I am very confused about when you would transform data given that it seems counterintuitive!
I would like to know more about transforming data. I know that for parametric statistics data needs to be normally distributed, but I am confused about when this does and does not apply.
Doesn't transforming data to make it normally distributed hide any experimental effects you have?
I have ran an experiment which should have resulted in differences in responding to questionnaire items. My hypothesis predicts a certain pattern of responding (e.g. higher ratings vs lower ratings) on a set of items for participants in different conditions. If I normalise the data to get rid of any skew towards lower or higher ratings, am I just going to hide any experimental effects? E.g. if group one averages a score of 7 out of 10 on an item while group two averages a score of 3/10 and then I normalise it so they both have similar means.
I am very confused about when you would transform data given that it seems counterintuitive!