Are Transformations of Data Changing the P-P Plots?

AI Thread Summary
Transformations of data, such as Ln, Log10, and square root, may not always change P-P plots, especially if the original data is already normally distributed or if the transformations are not suitable for the data. The lack of change in P-P plots suggests that the transformations applied did not significantly alter the distribution. It is crucial to select transformations based on the specific characteristics of the data, as not all transformations guarantee a shift towards normality. Additionally, assessing normality should involve multiple measures, including skewness and kurtosis, rather than relying solely on P-P plots. Understanding these aspects can enhance the analysis of data transformations in SPSS.
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I have recently just been given a computer lab task and that is to research transformations on the net and write a 1 page essay about them, which i am finding hard to find information on them, but anyway, here is my problem. We are required using our classes data to do transformations of our data for AGE, HEIGHT, WEIGHT in SPSS. now i have done the transformations, however we must also do P-P Plots to show what the transformations have done. All the transformations i have done, Ln, Log10, Square root, of these variables, have all come back with the exact same P-P plots as the original data from the normal variables. I was wondering is this supposed to happen, because i thought transformations could make non-normal data sometimes normally distributed, whereas mine does not change at all.

Any help on this would be greatly appreciated.
 
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maccaman said:
I have recently just been given a computer lab task and that is to research transformations on the net and write a 1 page essay about them, which i am finding hard to find information on them, but anyway, here is my problem. We are required using our classes data to do transformations of our data for AGE, HEIGHT, WEIGHT in SPSS. now i have done the transformations, however we must also do P-P Plots to show what the transformations have done. All the transformations i have done, Ln, Log10, Square root, of these variables, have all come back with the exact same P-P plots as the original data from the normal variables. I was wondering is this supposed to happen, because i thought transformations could make non-normal data sometimes normally distributed, whereas mine does not change at all.

Any help on this would be greatly appreciated.
The graphs should be different. Unfortunately, without seeing what you've done or the results therefrom, it's difficult to help. Can you provide more details concerning your transformations and provide images of the graphs??

To provide images of your graphs, upload to the site shown below and reference the URL's it provides.
http://www.imageshack.us


~~
 


It is possible that transformations of data can change the P-P plots, but it ultimately depends on the type of transformation and the data being used. In your case, it seems that the transformations you have applied (Ln, Log10, Square root) have not significantly changed the distribution of your data. This could be because your original data was already normally distributed or because the transformations were not appropriate for your data.

It is important to note that transformations are not a guaranteed method for making non-normal data normally distributed. They can help in some cases, but they should be carefully chosen and applied based on the characteristics of the data. In your case, it may be helpful to consult with your instructor or a statistician to determine if there are other transformations that could better suit your data.

It is also important to consider that P-P plots are just one way to assess the normality of data. It would be beneficial to also look at other measures of normality, such as skewness and kurtosis, to get a more comprehensive understanding of the distribution of your data.

In summary, while transformations can potentially change the P-P plots, it is not always the case. It is important to carefully choose and apply transformations based on the characteristics of the data, and to also consider other measures of normality in addition to P-P plots.
 
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