Are Transformations of Data Changing the P-P Plots?

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SUMMARY

The discussion focuses on the application of data transformations (Ln, Log10, Square root) in SPSS to the variables AGE, HEIGHT, and WEIGHT, and their effect on P-P plots. The user observed that the P-P plots remained unchanged after applying these transformations, raising questions about the effectiveness of the transformations. It was concluded that transformations do not guarantee a change in data distribution and that the original data may have been normally distributed or the transformations inappropriate. Additionally, alternative measures of normality, such as skewness and kurtosis, should be considered alongside P-P plots.

PREREQUISITES
  • Understanding of SPSS for data analysis
  • Knowledge of statistical transformations (Ln, Log10, Square root)
  • Familiarity with P-P plots for assessing normality
  • Basic concepts of skewness and kurtosis
NEXT STEPS
  • Research alternative transformations for non-normally distributed data
  • Learn how to interpret skewness and kurtosis in data analysis
  • Explore the use of Q-Q plots as an alternative to P-P plots
  • Consult statistical literature on the effectiveness of various transformations
USEFUL FOR

Statisticians, data analysts, and students working with SPSS who are exploring data transformations and assessing normality in their datasets.

maccaman
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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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