The first question that came to mind when I started this video was, How do I know if the variable is skewed. And then BOOM you covered it, Great thanks Analyze>descriptives>explore>histogram
Very Helpful and informative video.Thanks. But I have a small doubt, what to do if there are negative or 0 values in the data set when it is negatively skewed..?..
Dear Dr. Grande Supposed, it is not necessary that the response variable (dependent variable) be normally distributed. But the predictors (independent variables) need to be normally distributed. Thanks
Hi Todd Great video! It helped me a lot with my analysis. I followed the method of log transformation as mentioned by you, however i am writing a master's thesis and need to cite proper literature before adopting proper methodology. Do you, by any chance, have an academic article using this methodology which i can quote in my thesis? It would be of great help if you could share such literature with me. Thanks in advance! Regards Udita Agarwal
Great Video, but I have a question. If I have 3 data variables. One of these variables has a value of zero. Then do I have to use LOG10 (variable + 1) for all variables or only for variables that have a value of zero?
Thanks for this tutorial Dr Grande. My variables are now all within normal limits. However, I was wondering if there is a standard procedure for re-reflecting reflected square root/ Log transformed data so that I may interpret my ANOVA results accurately? At the moment the relationships are not in the expected directions due to the reflections.
First of all, thanks for your video! I have a quick question. Is it possible to first do a reflection, then do a LOG transformation? In other words, can we do two transformations on the same data set? Thank you.
Hey! Did you ever find out what to do? I've just run into the same problem, log10 worked great on one variable but on another variable it still remains skewed.
Thank you it was a great help. I have a question. Should transformation be applied only on variables that are not normally distributed or all the variables in a data set? For example, my data set contains different proteins each having numbers of samples. However, some of these proteins do not show normally distribution. So should I only transform them or all the proteins?
But why are you not considering Shapiro-Wilk and Kolmogrov-Sminov in test for Normality, or its not necessary? thank you for the educative presentation.
Hello Dr Todd, thanks for making this video. It has been helpful. I have a question Sir. To subject 4 different groups to the same parametric analysis, I found that, there were outliers and they violated the normality assumption. And so as I try to transform, I am checking for skewness and kurtosis, normality and equal error variances as they obeyed other parametric test assumptions. From your explanation, I need to observe the skewness and kurtosis values of the raw data before I perform a log10 transformation as this will help me know which data is negatively skewed and which is positively skewed. Now my question is, is it right (not biased) to subject say group 1 to LOG10 transformation using the positively skewed transformation method and subject group 2 to log10 transformation using the negatively skewed t. method (which is LOG10 (max value +1- x) where x is the distinct raw value in each cell) and then compare both data using the same parametric test. Say subjecting these two groups which had undergone different LOG10 transformation to ANOVA. Am sorry for typing so long Dr. I just wanted my question to be well understood. I await your prompt response. Thank you.
Qno.1 I have 3 dependent variables. Two of them are in range of normal skewness value i.e. +1 to -1 and have kurtosis in range of +3 to -3, but the third remaining dependent variable is not in normal range of skewnes or kurtosis. I want to transform that variable with square root transform to run parametric tests. So the question is, Can I transform that one variable only and run parametric test on the variables or I should transform all three variables before doing test? should I transform all three variables together even the two of them are already normally distributed? will it create problems to transform only one non normal variable? q.no.2 Can I infer and interpret my data for normality on the basis of skewness and kurtosis only rather than gooing for shapiro wilk test?
Thanks, Dr. Grande. Question: After I run an ANOVA on the transformed data, how do I interpret the results? For example, none of the means for the transformed data match the original data. Do I just go by the descriptive stats from the original data when reporting my findings?
i think you should report the mean and standard deviation from the original data. the transformation is done to satisfy the test requirements and to obtain the p value. I think so
HI Todd.. thanks for the video. I have a question regarding the transformation. Should I transform the items that make up the construct or first compute the construct from the items and then transform it. In your case, if we are measuring substance use with four items in a questionnaire, should we check the normality for each item or compute the score for the construct first. Appreciate your feedback. Thanks
I have noticed in your data that after doing the constant on the variable, the transformed variable still had the zero; in this case, two zeros? And If it's supposed to add a '1', shouldn't all data points be increased by it?
Hi Todd! Great video! It will surely help in my PhD tesis. Just one question: What to do when one sample group is normal distributed and all of the others are left skewed? I want to evaluate variability using ICC.
Hi Dr Grande, great video! Could I please ask few questions: if i do a log transform of my data for one way ANOVA, when I report the results would I then need to backtransform everything including the F ratio? Also do I present in a graph my raw untransformed data or my transformed data? Thank you so much!
Thank you for the video, but why would I transform my metric variables at all? If my sample includes more than 30 people, I can assume the central limit theorem anyway. It doesn't matter whether my variable is normally distributed in the present sample or not.
what do you do if some variables are positively skewed and some are negatively skewed? e.g in a questionnaire comparing different questions to each other one question is pos. skewed and the others all negative? Thanks in advance!
Todd, Thank you for your video. It's really helpful. I was just wondering if we can transform data with bimodal distribution to normal distribution as well?
Thank you; your vedio helped me so much as a new user; further; I ask in case of +ve skew; When I use exp; ln; log 10, sqrt or trunc? What the base of choice between them? Is transformation formula of -ve skweness is the same? I mean: exp(max + 1 - Varable); Log10 (max + 1 - Varable); trunc (max + 1 - Varable) and so on?
Hi Todd.thanks for the video .it is extremely helpful.i have a negatively skewed data and transformed through sqr reflect but its sgnificance is still less than .05.and it is still negative skewed .please tell me how can i transform it .i have taken log also but still no use.i will b thankful if u could help me out.
Good afternoon My field of study employs categories that are not evenly spaced, ie, 25,50,100,200,400. These intervals are regularly used in literature to class achieved results in grouting. Does this spacing for constitutes a constrain in statistical analysis of results? Frequent values obtained are positive skewed. What Log base should better be used? BR
Do you have any reference for the transformation of negative number we should add a value greater than it for log? Like -3 you took log value +4 ? Any research paper please??
Sir, I beg for your help. I have 3 factors and variable 3, OD, pH and Sulphate are the parameters. I have done a normality test with Kolmogorov-Smrinov but all three data are not normal, then I transformed and I retested its normality, but 1 data is not normal, 2 data are normally distributed. Abnormal data has negative skewnes and there is no outliner on the boxplot. What statistical tests should I do for normal data and abnormal data?
Hello, I had a positive skewness of a variable of 1.920 and when I transformed using Log10 it just changed it to skewness of 0.9. Is this because I have a lot of repeat data point values?
Hey Todd, Once I have log transformed my data, I will go on to do some t-tests and anova, how do I write the results to indicate that the data used have been log transformed? Also some conditions of my experiment are normally distributed, so is it ok to log transform some and not others? Are they directly comparable? Thank you.
do you have to do the same transformation to your data is you want to do mixed design anova afterwards e.g. if they're all positively skewed by one variable has a zero value, do they all have to transformed by +1 and log10?
Hi Dr Grande, I have conducted a log10 and square root and the variables are still not normal, what should I do? I also have to conduct a parametric test (Multiple Regression)
When I use the method for transforming negatively skewed variables, it reverses the skew to positive and seems to reverse the scores as well. Short of reverse-scoring these variables when they don't need to be, is there a way around this? Or am I doing something wrong? I have tried all methods in this video and nothing is working.
thanks for the excellent review. However, once I've done my reflection (reverse score transformation), how do I change the numbers back ? (Field, 2009)? heidi
HELLO ,ONCE i have already transformed my data into a normally distributed data set, how will i able to use those obtained data in data analysis? for instance is in multiple regression analysis wherein an equation model will be created. What will happen to the independent variables? can dependent variable be predicted using the original data value of the independent variables??
did you try other transformations aswell? log10 is rather suitable for variables which are only slightly skewed. for stronger skewness, other transformations might work better, like sqrt (google is your best friend). If your data still remains not normally distributed, you should use non-parametric approaches for analysis.
Good People, Should I transform all variables or just those which are non-normal distributed? If later I am going to use all of them in one model of SEM?
HI, could you please provide a citation that uses the absolute value of 1 as the cutoff for skewness? I need it for an article and am having a hard time locating one. Thanks!
The first question that came to mind when I started this video was, How do I know if the variable is skewed. And then BOOM you covered it, Great thanks Analyze>descriptives>explore>histogram
great video, you should live forever
Thank you and thanks for watching -
Thank you so much, Dr. Grande!! Your Video helped me so much with my statistical issue during my bachelor thesis.
Very Helpful and informative video.Thanks.
But I have a small doubt, what to do if there are negative or 0 values in the data set when it is negatively skewed..?..
Thank you for tutorial. Gratitude from Nepal.
Dear Dr. Grande
Supposed, it is not necessary that the response variable (dependent variable) be normally distributed. But the predictors (independent variables) need to be normally distributed.
Thanks
Thank you so much. This is a great help. God bless you.
Hi Todd
Great video! It helped me a lot with my analysis. I followed the method of log transformation as mentioned by you, however i am writing a master's thesis and need to cite proper literature before adopting proper methodology. Do you, by any chance, have an academic article using this methodology which i can quote in my thesis? It would be of great help if you could share such literature with me.
Thanks in advance!
Regards
Udita Agarwal
Thank you for showing how to do the Log10 transformation and walking through the steps.
Great Video, but I have a question. If I have 3 data variables. One of these variables has a value of zero. Then do I have to use LOG10 (variable + 1) for all variables or only for variables that have a value of zero?
I guess that the answer is to apply such correction to ALL the variables
Thanks for this tutorial Dr Grande. My variables are now all within normal limits. However, I was wondering if there is a standard procedure for re-reflecting reflected square root/ Log transformed data so that I may interpret my ANOVA results accurately? At the moment the relationships are not in the expected directions due to the reflections.
First of all, thanks for your video! I have a quick question. Is it possible to first do a reflection, then do a LOG transformation? In other words, can we do two transformations on the same data set? Thank you.
Hi! Great video - what do you do if your data is still skewed after using a log10 transformation?
Hey! Did you ever find out what to do? I've just run into the same problem, log10 worked great on one variable but on another variable it still remains skewed.
This video was very helpful, thankyou.🙏
Thank you it was a great help. I have a question. Should transformation be applied only on variables that are not normally distributed or all the variables in a data set? For example, my data set contains different proteins each having numbers of samples. However, some of these proteins do not show normally distribution. So should I only transform them or all the proteins?
But why are you not considering Shapiro-Wilk and Kolmogrov-Sminov in test for Normality, or its not necessary? thank you for the educative presentation.
Thank you for the video. I used the metod for 0, but after the change my kurtosis became negative. Do you have any suggestions on that?
Hello Dr Todd, thanks for making this video. It has been helpful. I have a question Sir.
To subject 4 different groups to the same parametric analysis, I found that, there were outliers and they violated the normality assumption. And so as I try to transform, I am checking for skewness and kurtosis, normality and equal error variances as they obeyed other parametric test assumptions.
From your explanation, I need to observe the skewness and kurtosis values of the raw data before I perform a log10 transformation as this will help me know which data is negatively skewed and which is positively skewed.
Now my question is, is it right (not biased) to subject say group 1 to LOG10 transformation using the positively skewed transformation method and subject group 2 to log10 transformation using the negatively skewed t. method (which is LOG10 (max value +1- x) where x is the distinct raw value in each cell) and then compare both data using the same parametric test. Say subjecting these two groups which had undergone different LOG10 transformation to ANOVA.
Am sorry for typing so long Dr. I just wanted my question to be well understood. I await your prompt response. Thank you.
hello, thanks for the video! helps a lot:)
does the independent variable following the same instructions? or Skewness only for dependen variable?
Qno.1
I have 3 dependent variables. Two of them are in range of normal skewness value i.e. +1 to -1 and have kurtosis in range of +3 to -3, but the third remaining dependent variable is not in normal range of skewnes or kurtosis. I want to transform that variable with square root transform to run parametric tests. So the question is, Can I transform that one variable only and run parametric test on the variables or I should transform all three variables before doing test? should I transform all three variables together even the two of them are already normally distributed? will it create problems to transform only one non normal variable?
q.no.2
Can I infer and interpret my data for normality on the basis of skewness and kurtosis only rather than gooing for shapiro wilk test?
Thanks, Dr. Grande. Question: After I run an ANOVA on the transformed data, how do I interpret the results? For example, none of the means for the transformed data match the original data. Do I just go by the descriptive stats from the original data when reporting my findings?
i think you should report the mean and standard deviation from the original data. the transformation is done to satisfy the test requirements and to obtain the p value. I think so
Yes I have this same doubt. Once the data has been transformed, how do you interpret the results?
Clear explanation. Easy to follow. Thank you.
HI Todd.. thanks for the video. I have a question regarding the transformation. Should I transform the items that make up the construct or first compute the construct from the items and then transform it. In your case, if we are measuring substance use with four items in a questionnaire, should we check the normality for each item or compute the score for the construct first. Appreciate your feedback. Thanks
I have noticed in your data that after doing the constant on the variable, the transformed variable still had the zero; in this case, two zeros?
And If it's supposed to add a '1', shouldn't all data points be increased by it?
My data is still negatively skewed even after log10 transformation (-640), which test shall I use: parametric or non parametric ? thank you
Great video, thanks a lot Todd!! I have a question about adding values when there is a negative value. If the negative value is -2.56, do I add 3.56?
Hi Todd! Great video! It will surely help in my PhD tesis. Just one question: What to do when one sample group is normal distributed and all of the others are left skewed? I want to evaluate variability using ICC.
Hi Dr Grande, great video! Could I please ask few questions: if i do a log transform of my data for one way ANOVA, when I report the results would I then need to backtransform everything including the F ratio? Also do I present in a graph my raw untransformed data or my transformed data? Thank you so much!
So should you from now on use the Log variables in further analysis?
Is the reflection transformation described in the literature? Can I find a paper to cite?
you are getting me through my stats Todd so huge thanks
You are quite welcome!
Hello, should we mention in our research work that we transformed the data by log10? is it manipulation of data or is it normal to do so?
Thank you for the video, but why would I transform my metric variables at all? If my sample includes more than 30 people, I can assume the central limit theorem anyway. It doesn't matter whether my variable is normally distributed in the present sample or not.
Thank you for the video, it is very useful.
what do you do if some variables are positively skewed and some are negatively skewed? e.g in a questionnaire comparing different questions to each other one question is pos. skewed and the others all negative? Thanks in advance!
Todd, Thank you for your video. It's really helpful. I was just wondering if we can transform data with bimodal distribution to normal distribution as well?
bless this man
Thank you; your vedio helped me so much as a new user; further; I ask in case of +ve skew; When I use exp; ln; log 10, sqrt or trunc? What the base of choice between them? Is transformation formula of -ve skweness is the same? I mean: exp(max + 1 - Varable); Log10 (max + 1 - Varable); trunc (max + 1 - Varable) and so on?
Très intéressant surtout la deuxième partie merci pour le partage.
Thanks for the video. After the transformation, what can I say about the original data based on the lambda?
Hi Todd.thanks for the video .it is extremely helpful.i have a negatively skewed data and transformed through sqr reflect but its sgnificance is still less than .05.and it is still negative skewed .please tell me how can i transform it .i have taken log also but still no use.i will b thankful if u could help me out.
Good afternoon
My field of study employs categories that are not evenly spaced, ie, 25,50,100,200,400. These intervals are regularly used in literature to class achieved results in grouting. Does this spacing for constitutes a constrain in statistical analysis of results? Frequent values obtained are positive skewed. What Log base should better be used?
BR
Do you have any reference for the transformation of negative number we should add a value greater than it for log? Like -3 you took log value +4 ? Any research paper please??
Sir, I beg for your help. I have 3 factors and variable 3, OD, pH and Sulphate are the parameters. I have done a normality test with Kolmogorov-Smrinov but all three data are not normal, then I transformed and I retested its normality, but 1 data is not normal, 2 data are normally distributed. Abnormal data has negative skewnes and there is no outliner on the boxplot. What statistical tests should I do for normal data and abnormal data?
Every video shows only one variable. I have 60 variables. Should I do it manually one by one or is there a one click solution for multiple variables?
Hello, I had a positive skewness of a variable of 1.920 and when I transformed using Log10 it just changed it to skewness of 0.9. Is this because I have a lot of repeat data point values?
Very informative thank you.
Thanks for this video....em doing regrrestion n the value of R is 0.78 so how can I improve this value ????
This was very helpful. Very clarifying, thank you.
Hey Todd, Once I have log transformed my data, I will go on to do some t-tests and anova, how do I write the results to indicate that the data used have been log transformed? Also some conditions of my experiment are normally distributed, so is it ok to log transform some and not others? Are they directly comparable? Thank you.
do you have to do the same transformation to your data is you want to do mixed design anova afterwards e.g. if they're all positively skewed by one variable has a zero value, do they all have to transformed by +1 and log10?
Hi Dr Grande,
I have conducted a log10 and square root and the variables are still not normal, what should I do? I also have to conduct a parametric test (Multiple Regression)
When I use the method for transforming negatively skewed variables, it reverses the skew to positive and seems to reverse the scores as well. Short of reverse-scoring these variables when they don't need to be, is there a way around this? Or am I doing something wrong? I have tried all methods in this video and nothing is working.
for negatively skewed data transformation, you can skip to 10:37
thanks for the excellent review. However, once I've done my reflection (reverse score transformation), how do I change the numbers back ? (Field, 2009)? heidi
HELLO ,ONCE i have already transformed my data into a normally distributed data set, how will i able to use those obtained data in data analysis? for instance is in multiple regression analysis wherein an equation model will be created. What will happen to the independent variables? can dependent variable be predicted using the original data value of the independent variables??
Thank you so much, Sir
can we use multiple methods of transformation for different multiple of one dataset??
One question, is there any limit in terms of the negative value? e.x. -100000. Can I just ad 100001?
Yes, this is super helpful!
Thank you for making this video!!
Bless your heart!!~
Helpful in understanding transformations.
Hi. Could you tell me how to solve the problem of inverted signs (positive/negative) of the outer weight (Path coefficients) in Smart PLS. Thank you
Sir, I tried this. It transformed my data from positive to negatively skewed. What to do in such cases?
Dear Todd, and if after the log10 or sort, the variables continue with skewness what to do?
please let me know if you had answer
did you try other transformations aswell? log10 is rather suitable for variables which are only slightly skewed. for stronger skewness, other transformations might work better, like sqrt (google is your best friend). If your data still remains not normally distributed, you should use non-parametric approaches for analysis.
Good People, Should I transform all variables or just those which are non-normal distributed? If later I am going to use all of them in one model of SEM?
only non-normal ones
thank you!
What should we do if after the first transformation of the positively skewed data doesn't respond?
HI, could you please provide a citation that uses the absolute value of 1 as the cutoff for skewness? I need it for an article and am having a hard time locating one. Thanks!
Thank you.
Sincerely,
Visual Learners
Very helpful. Thanks!
thank you'
One thing is not clear to me: why you don't differentiate between groups? Shouldn't you check for normality within groups?
My skewness and kurtosis values are between 1 and -1 but Shapiro-Wilk test and Kolmogorov-Smernov test are significant ... help?!
I have the same problem. Skewness seems to be fixed going by this wonderfull video, but the SW and KS is still ,000. Can anyone help?
Hi, what is my skewness is 0.08 ?
how can we contact Dr. Grande?
hi
(can you explain the (relative sufficiency)
merci *_*
You're welcome!
Hi - yep but its so quiet
Please improve your audio, can barely hear you