There are numerous ways to test normality: 1)Mean = median, skew = 0, kurtosis = 0: all that information is automatically outputted in the data audit node.
2)Run the Kolmogorov-Smirnov Test or Shapiro-Wilk Test (if the test is non-significant (p>0.05) then the distribution of the sample is not significantly different from a normal distribution. If the test IS significant (p
The disadvantage is that in large samples, these tests can be significant even when the scores are only slightly different from a normal distribution. Shapiro-wilk is more powerful. This is done in the Statistics Output node under Explore.
It isn't that there is no significance... it is that "it wasn't shown to be significant at the .05 level" if it barely is less than .05 you can say it is marginally significant and if it is slightly greater you can say marginally not significant.
Not bad, but it would be nice if you didn't zip through the intermediary steps so fast... and maybe provided a little more explanation. Also, the cursor is sometimes moving too fast to see what you are actually clicking on...
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Loved this brief tutorial. Thank you!
There are numerous ways to test normality:
1)Mean = median, skew = 0, kurtosis = 0: all that information is automatically outputted in the data audit node.
2)Run the Kolmogorov-Smirnov Test or Shapiro-Wilk Test (if the test is non-significant (p>0.05) then the distribution of the sample is not significantly different from a normal distribution. If the test IS significant (p
3) Check the P-P Plot (should be approximately 45 degree slope), also done in the Statistics Output Node under Explore.
Great presentation. Great work. Thank you.
Gracias por su aporte, ustedes creen que puedan subir mas material de clementine.
very helpful. Thanks
Awesome video, thanks!
Great demonstration
The disadvantage is that in large samples, these tests can be significant even when the scores are only slightly different from a normal distribution. Shapiro-wilk is more powerful. This is done in the Statistics Output node under Explore.
Can we give only continous data as Target for Auto numeric model? I dont get to see many fields in that.. all I see is only continous data
Was this from a webinar? The audio sounds so compressed.
I learned a lot thank u :)
Hi, could you share the dataset used in the video?
Great talk,. keep it up
Really helpfull, thanks
can you help to how i add a Decision in generated report ?
a Decision Tree *
please where can I get a free copy of ibm spss modeler to practice all of this and thank you
hihi
possible to share the ppt?
Thank you
kool, u r awsome....
awesome
Please share a site where i can download spss modeller for free. maybe a crack
It isn't that there is no significance... it is that "it wasn't shown to be significant at the .05 level" if it barely is less than .05 you can say it is marginally significant and if it is slightly greater you can say marginally not significant.
Not bad, but it would be nice if you didn't zip through the intermediary steps so fast... and maybe provided a little more explanation. Also, the cursor is sometimes moving too fast to see what you are actually clicking on...