Thanks for the feedback. Glad it helped!

SPSS is the fucked

My pleasure. Thanks for your kind words.

Glad it was helpful!

Sorry for the late reply and the need to say no. The dataset I use here is just for my class.

Hi! My pleasure. Nominal variables should not be used with Spearman. If age has been chunked into 3 or more groups, it would be an ordinal variable as well and Spearman could be used. If age is just two groups, you would want an independent samples t-test or a point-biserial correlation.

My pleasure! Best wishes to you!

My pleasure - glad it helped!

Very cool! Glad I could help - hope your test went well!

Hooray!

My pleasure! That is very kind of you to say.

My pleasure!

My pleasure!

My pleasure. Glad you found it helpful.

Spearman would be more flexible and appropriate in this case - it can handle lumpy data better than Pearson

From my understanding, statisticians disagree here. Some say it is OK to use a histogram for ordinal data (see, for example, sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_summarizingdata/bs704_summarizingdata4.html#:~:text=When%20one%20is%20dealing%20with,categories%20have%20an%20inherent%20order). Others say you should not use a histogram for ordinal data and should use a bar chart or box-and-whisker plot instead (www.uni-bamberg.de/fileadmin/eng-ling/fs/Chapter_19/411Frequencydata.html).

@@virginiawickline2609 You rock! Thanks a lot. Appreciate the sources too :)

My pleasure! Absolutely a normality test is appropriate. I run out of time to also teach this during my class (which is the primary audience for this video), but if I were doing it myself for research, I would rely on a K-S (Komolgorov-Smirnov) test myself.

@Virginia Wickline So, if the normality is violated, then the spearmen coefficient is a suitable alternative for pearson to make the correlation or not mandatory

@@fadhilfp6 If normality is violated, Spearman is more appropriate. For more, see: stats.stackexchange.com/questions/3730/pearsons-or-spearmans-correlation-with-non-normal-data

Thanks, Katie! Glad it was helpful

I apologize for missing your comment. I do not have an article on hand to suggest. Sorry!

@@virginiawickline2609 ok.. Thanku very much mam for your reply

Hi Golam, with regrets, no. The dataset is used in my classes and is kept private since they helped fill out the items.

So glad this helped!

Hi Coco - haha. Maybe not - but it is useful! ;)

My pleasure! Thanks for checking it out! :)

Hi Dopeee, thanks for checking out my videos. I appreciate your comment and need to kindly decline. My videos are primarily designed for students in my class with the dataset we use, so I need to keep the variables shown to help them.

Hooray! :)

My pleasure, John! Thanks for checking it out.

Thanks for the feedback, Tyler! Happy to be of service.

Hi! I sometimes still plot a regression line or a Loess curve to see where the data change directions. I am open to options/suggestions from other viewers!

My pleasure :)

Hmm...have you also considered removing outliers (high Cook's D value) or cases with high leverage?

@@virginiawickline2609 is it normal to remove it. I am about to consider this variable as dependent one. It was behaving like poisson but with this behavior it doesn't respect poisson assumption either.

@@phd.eriolamariuscharlotade5634 Hi! You are reaching the limits of my knowledge. However, it is fairly common to remove cases with high Cook's D values so you are removing the influence of outliers. See, for example: towardsdatascience.com/identifying-outliers-in-linear-regression-cooks-distance-9e212e9136a

Glad to hear - thanks! :)

Oops - sorry! Thanks for the feedback! This segment covers making a continuous (ratio) variable into two chunks (nominal). I will work on shooting a new video very soon for reverse scoring.

Many thanks, Najla, for your kind words. So glad it was helpful!

My pleasure, Najla!