# transformation

1. ### Regression with sqrt transformed dependent variable - meaning of the model's B value?

Hi fellow nerds :) My dependent variable had to be transformed by square root (so the residual plot would be normal). I usually use log10 transformations and then the B value (slope) translates into the percents of the dependent variable, but what do I read from a B=-,499 (P=0,015) of a...
2. ### Should you transform skewed data when the distribution is expected?

Hi all, I have been discussing this topic all week with people in my department and I can't seem to get a straight answer. I also tried posting this thread in a non-psychology forum and received only a few straight of the textbook responses about positive skew. I was taught long ago that you...
3. ### Should you transform skewed data when the distribution is expected?

Hi all, I have been discussing this topic all week with people in my department and I can't seem to get a straight answer. I was taught long ago that you should not necessarily transform a variable if the population distribution is expected to be skewed (for use in regression analysis). For...
4. ### Descriptive Summations

How would I go about solving this? 1/nΣxi^2=100 and 1/nΣxi=2. Define yi=2xi+1 and find 1/nΣyi^2.
5. ### Transforming two non-normal sets of data for 2 sample t-test?

Hey all, Ok so I'm trying to compare the means of two sets of data using a 2-sample t-test. Unfortunately, both sets of data are non-normal. It appears box-cox or Johnson transforms will work, but my question is, wouldn't I need to transform both sets of data using the same transform...
6. ### Linear Transformation Problem

Hi there, Basically, I am checking for outliers in a 'frequency of use' construct measured in number of weeks. Since the box plot was right-skewed, i conducted a log transformation via spss. Although, the result seemed fine but now I want to create boxplots for other constructs which are...
7. ### predicting discrete variable (age) from continuous data and transformations

Hi, i have data on age (years) and a continuous variable (weight for example). I want o predict the age using a linear regression. However, i understand that age is discrete and therefore may not be directly used. So i log transformed both the age and the weight but now i checked the residuals...
8. ### Transformations

I have two datasets, before and after the application of a treatment. The treatment is theorised to produce an increase in "factor x", and difference between the two datasets should be a positive value, however due to noise/error etc in the data some of the difference values are negative. In...
9. ### log transformation of binary variables

Hi everyone, I am trying to do a factor analysis of a group of drinking behavior variables, and some of them are highly positively skewed. I want to do a log transformation of these variables, but they are binary. I can't find anything that deals with whether this is a problem or not - but...
10. ### Should I transform my response data (count data)? Impact on subsequent analyses?

Hello, My response variables are derived from count data. I have the biennial winter population counts of a hibernating mammalian species (sites / n =226). My predictor variables are from two time steps (i.e. 1992 and 2001). I created my response variables from the following to correspond...
11. ### Cyclical Data Transformation

For data that may look linear but is in fact cyclical (time most commonly), is there like a sine function based data transformation that has been proven to work well? I feel kinda silly making dummy fields, and now that I'm playing around with multiple imputation, I'm worried that if I'm missing...
12. ### Confusion on what level should data follow normality

Hi everyone. I'm experiencing some confusion as to what level the data should be normal. For instance, in an unpaired data set, where some vitamin is the main factor (given or not given) applied to a population of mice, you are interested if their blood sugar level is differing between the...
13. ### Apply a transformation to distrubition?

Hello all, I'm doing upwind/downwind comparisons for air quality data. I recieved some feedback yesterday (thanks Simon!) that a paired t-test would probably be an appropriate way to compare hourly averages from two sites located about 1km apart. Also, that the data set is probably large...
14. ### Clinical trial analysis - have I got it right?

Two-way ANOVA (with replication), how robust is robust? Hello all, I would like to see what the pain of a patient is before and after an opperation. But my data is not fitting the assumptions of ANOVA. I have read that ANOVA is robust, but how robust? I have data from patients who were...