KS is a goodness of fit test. In any GOF test, you will find observed data and expected data. So y here is your observed data set and pnorm is the expected data set. Hence it is required for you to write the pnorm argument so that you will have something to test your goodness of fit against. I hope this helps.
You can use the Kolmogorv-Smirnov test to check various distributions. If you wanted to check whether your data came from a Poisson distribution you would have put the "ppois" argument exponential distribution --> "pexp" uniform distribution --> "punif" and so on
Hi. I have continuous data such that there are two groups (normal and abnormal spine) i.e. there are continuous type readings in each category. I tried to run ks test on both datasets in both Rstudio and SPSS but I get different results. SPSS results abnormal category: p=0.2 normal category: p=0.037 RStudio results abnormal category: p
Wrong? We should test the normality of *residuals* not the data. For example - shapiro.test(model$residual) It was what I learnt from school. Please, correct me.
@@CrackEconomicsandStatistics Thanks for your comment, do you have a tutorial to compare normality test on t-test and simple linear regression? Thanks!
Clearly explained
Thanks. Kindly share it with others.
Excellent Job, Prof.
Keep it up.
Thanks!
Sir, Is there any problem to use ks test if the observations are repeated?
Thank you Man.
Hi thank u .
Wht is interpretation of W in shapiro and D in ks
Sir can you share the reference for ks test used for more than 100 obs. ?
Subtitles disturbing and cannot see below written things
Perfect video
Thanks!
nice explain
Great video... thank you. Quick question, why did we use the argument "pnorm" in the Kolmogorov-Smirnov test?
That is the command.
KS is a goodness of fit test. In any GOF test, you will find observed data and expected data. So y here is your observed data set and pnorm is the expected data set. Hence it is required for you to write the pnorm argument so that you will have something to test your goodness of fit against. I hope this helps.
@@manasiwalimbe8960 It more than helps. Thank you so much!
You can use the Kolmogorv-Smirnov test to check various distributions.
If you wanted to check whether your data came from a Poisson distribution you would have put the "ppois" argument
exponential distribution --> "pexp"
uniform distribution --> "punif"
and so on
This is really helpful!!
Thanks.
Can you do a video on qqplot and skewness
I will try.
hello so the default alpha in r studio is 0.05?
Yes...
If you wish to change use the following command
conf.level = 0.90
By default it is 0.95.
@@CrackEconomicsandStatistics Thank you!
Love you sir👌...but please give option to offline download
Thanks.
Why normality tests? Why dont we implement poissonity test? What makes normal distribution privileged among other distributions?
Because it is hypothesized that in the real world, as the sample sizes increases, they follow a normal distribution.
Hi. I have continuous data such that there are two groups (normal and abnormal spine) i.e. there are continuous type readings in each category. I tried to run ks test on both datasets in both Rstudio and SPSS but I get different results.
SPSS results
abnormal category: p=0.2
normal category: p=0.037
RStudio results
abnormal category: p
This is strange. Let me check.
@@CrackEconomicsandStatistics sure, let me know if you want me to pass on the dataset to you (I can email it to you)
Yes please.
@@CrackEconomicsandStatistics email id?
crack.eco.stat@gmail.com
Wrong? We should test the normality of *residuals* not the data. For example - shapiro.test(model$residual)
It was what I learnt from school. Please, correct me.
That's applied to regression analysis.
This is helpful to identify whether we should use parametric or non-parametric tests.
@@CrackEconomicsandStatistics Thanks for your comment, do you have a tutorial to compare normality test on t-test and simple linear regression? Thanks!