A short video without leading into any confusion in spite of being premium member I'm patiently watching complete ads on your channel in incognito support you. way more videos on statistics Thank you
Thank you for your helpful explanation and plentiful examples. I especially appreciate the way you presented easy to understand examples of difficult terms.
The Mann-Whitney U is the nonparametric alternative to the Independent t-test. The Wilcoxon signed rank test is a nonparametric test that compares a group of numbers' medians to a hypothetical median. This test is mathematically equivalent to a Mann-Whitney U-test.
Hi As said that parametric test can be used when our data is normally distributed and non parametric when not normally distributed Also ratio and interval data parametric test applies snd for qualitative non parametric So what if my quantitative data that is ratio or interval is not normally distributed then cant we apply non parametric test as it is only applicable to qualitative data
@@edifoI still have lots going through my mind. Please if you throw some light on my queries 1. Do we consider nominal ordinal and interval scale as discrete and ratio as continuous 2. If we consider above three scale as discrete than does discrete probability distribution applies all three scale nominal ordinal and interval Or does it apply only to interval 3. Do we look for normality for nominal ordinal and interval data as well Or is it only for ratio scale Then I am assuming in that case we apply only non parametric test to all three scale And parametric and non parametric to ratio based on the normality 4. Also assumption is made only for the population or also for sampling distribution I know it's a long list. It would be very kind of you if you can answer my queries please
Thank you for this, I was struggling to find an explanation that was simple and didn't require me to already know what all the different types of tests are and such. I just wanted a simple comparison, and this was perfect.
Honestly, I have learned a lot from this video, thanks a lot. But I have seen some researchers applying One-way ANOVA for data that's clearly ordinal... e.g. a Likert Scale data. Please, can u help with some explanation whether there are situations for that? Thank u.
Thank you for this. it is well- explained. This confirmed some of my unsure thoughts on inferential statistics , specifically on the parametric and nonparametric tests.
This is one of those videos that can summarize hours and hours of dull lectures in a concise, clear manner and in a short time. Thank you.
Glad it was helpful!
This is clear.
Exactly
Great video, analytical review of the subject in details that made it easy to understand
Glad it was helpful!
Great..and what a wonderful voice...
Thank you
Nice video.
Thank you
Thank you too
Thank you so much
You're most welcome
Thank you💛
You’re welcome 😊
🙏🙏
Keep watching...
A short video without leading into any confusion
in spite of being premium member I'm patiently watching complete ads on your channel in incognito support you.
way more videos on statistics
Thank you
Thanks for that!
Thank you for your helpful explanation and plentiful examples. I especially appreciate the way you presented easy to understand examples of difficult terms.
Glad it was helpful!
Most Welcome....
Also discuss on what is considered in deciding on what specific parametric test to be applied by the researcher
Sure.
it was a very nice explanation. but isint it that Wilcoxon rank sum test is the same as Mann Whitney U test???
The Mann-Whitney U is the nonparametric alternative to the Independent t-test. The Wilcoxon signed rank test is a nonparametric test that compares a group of numbers' medians to a hypothetical median. This test is mathematically equivalent to a Mann-Whitney U-test.
Hi
As said that parametric test can be used when our data is normally distributed and non parametric when not normally distributed
Also ratio and interval data parametric test applies snd for qualitative non parametric
So what if my quantitative data that is ratio or interval is not normally distributed then cant we apply non parametric test as it is only applicable to qualitative data
You can apply Non-Parametric.
@@edifoI still have lots going through my mind.
Please if you throw some light on my queries
1. Do we consider nominal ordinal and interval scale as discrete and ratio as continuous
2. If we consider above three scale as discrete than does discrete probability distribution applies all three scale nominal ordinal and interval
Or does it apply only to interval
3. Do we look for normality for nominal ordinal and interval data as well
Or is it only for ratio scale
Then I am assuming in that case we apply only non parametric test to all three scale
And parametric and non parametric to ratio based on the normality
4. Also assumption is made only for the population or also for sampling distribution
I know it's a long list. It would be very kind of you if you can answer my queries please
Please Watch this video, which explains about Data Types.
ua-cam.com/video/KnBik0ysvac/v-deo.html
Great and meaningful lecture. kudos
Thank you
well summarized and easy to understand lecture
Thank You..
I wish you would make another video about what statistical tests are appropriate for various sample researches.
Sure....
Useful video, thanks
Glad it was helpful!
wonderfully explained sir. pls make more videos on stats.
Sure I will. Keep Watching
concise and easy to digest
Thank you Very Much...
It is good lecture
Thank you..
If one assumptions fulfill second not can we do anova test .
E.g data are not normally distributed but there is homogeneity of variance groups
Normality of data is a prerequisite for parametric tests
Before applying anova we assume normality of data its homogenity of varriance we should not check
Normality and Homogeneity need to be checked for ANOVA
Thank you for this, I was struggling to find an explanation that was simple and didn't require me to already know what all the different types of tests are and such. I just wanted a simple comparison, and this was perfect.
Glad it helped!
Thank you sir
Welcome
Hello It is very helpful video. I would like to clarify this idea. I think the counterpart of Independent sample t-test is Mann-Whitney U test.
For normally distributed data, the independent t test can be used, and for non-normally distributed data, the Mann-Whitney U test can be used.
Really good
Glad you think so!
Thanks a lot!
You're welcome!
Thank you so much Sir, please how about Kolmogorov-smirnov test? It is so popular too.
Keep Learning.....
Sir.... In my dissertation can i use Likert scale, pie charts and Frequency( in my one single research Paper) without including hypothesis?
Of course you can.
But my suggestion is that try to use hypothesis, they it will increase the quality of your work.
Thanks
Welcome
Brilliant explanation, thank you!
Glad it was helpful! Keep watching, Keep learning...
Thank you for sharing your expertise about statistical tools
Glad it was helpful!
Thank you so much we need more videos related to research 🙏
We will
Honestly, I have learned a lot from this video, thanks a lot. But I have seen some researchers applying One-way ANOVA for data that's clearly ordinal... e.g. a Likert Scale data. Please, can u help with some explanation whether there are situations for that? Thank u.
Likert scale is purely ordinal data.
If you use Likert scale for a measuring a construct, you can treat it as scale data.
@@edifo U mean the Likert Scale can be used as interval/ratio scale as well? Wonderful...!
@@funnyclips2696 For a construct you can use Likert scale as scale data.
Very gainful. Thk u so much
Thank you...
Keep watching.
How we check population is normally distributed
In excel
In excel you can check the normality of distribution. Its a procedure. Normally NORDIST function is used for this.
It is better to use SPSS for this. Because the procedure is very easy.
@@edifo i dnt have spss .i use excel sir
@@mufazilali9294 No Problem, you can use excel for checking normality.
Excellent explantion
Glad it was helpful!
Good explanation
Thanks and welcome...
Keep Watching....
Thank you very much sir
Most welcome
Super voice sir
Thank you...
Keep learning
Keep watching..
Brilliant
Thank you
Keep watching...
Keep learning ....
👍🙏
🙏
Thank you for this. it is well- explained. This confirmed some of my unsure thoughts on inferential statistics , specifically on the parametric and nonparametric tests.
Glad it was helpful!
Keep watching...
Keep learning....