Understanding missing data and missing values. 5 ways to deal with missing data using R programming

In this video I talk about how to understand missing data and missing values. I also provide 5 strategies to deal with missing data using R programming. If you're doing quantitative analysis or statistical analysis, your dataset will almost certainly contain missing values. Dealing with missing data using R programming is easy and I provide a step by step approach. This is an R programming for beginners video.

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Twitter: @drgregmartin

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[fernleaf]

Great video. Looking forward to your videos about imputation and the MICE package. Keep’em coming!

[asiathogmartin]

You said, "Boom Shakalaka" LOL! Most awesome video ever.

[xprownz]

Great video, helped me a lot cleaning some datasets in an easy way.

[chertify]

I'm watching halfway. I just hit subscribe. The content you put here in this video is just so well-explained! You translate codes into layman's term and have "tidily" edited your video! I love the zoom in and out effect of it and the sound effect. Not too much. Just right. Not annoying, rather impressive. Thank you for sharing your knowledge to us, Greg!

[danmungai]

Hello sir, this is amazing. You're a wonderful teacher. Please do more. Very many thanks from me here in Kenya

[arifmemovic]

You have saved hundreds if not thousands of hours of beginning analysts time. Thanks!

[rezzyraptor]

I know this video is old, but still very helpful! I love your channel, you make stats and R fun :D Thanks for making these, keep up the great work.

[Junecode]

Greg, thanks for ALL your elaborate videos and the structure of the lessons. In addition, the way you explain the code methodically! Love it. I was so stressed about replacing NA with none for the variable, gender (Pt 3 of handling missing values), turns out the variable is sex. Phew

[adrianfletcher]

Please do a video on imputation in R! I was working on something and I was confused as to whether my data was "missing at random" or another option so I wasn't sure how to handle imputation.

[dineshlakshitha]

supper video
clear,
thank you soo much

[ostione]

Best r tutorial, visuals, pace, delivery....so good!

[eridianestrada]

Hello, thank you for these videos. They are very helpful. Is there a video on what program evaluation is and how that looks in the global health context?

[ousmanelom]

You are a good teacher i like your video

[jamesparker]

Hi Greg love your videos! Im a medical student who is going to intercalate next year in public health which im very excited about. Ive got a choice however between MSc International public health (with a focused stream on humanitarian studies) or MSc Humanitarian studies. Im interested in the working humanitarian relief space, but im wondering if I should I keep my studies a bit broader at the moment and study the MPH. Would be interested to know what you think in terms of if one would be more advantageous in my career. thanks James

[hazemshahin]

great way of yours to finally simplify stats ...thank you

[tuanlong]

11:48 - " Take care, stay well, don't do drugs, always do best, speak to you soon. Bye! " - that's a cool outro

[lilikoimahalo]

This is a very insightful explanation:) thank you!

[nour_hisham]

Thanks for the help, really appreciate, I have exam tomorrow, and you really helped Sir.😃❤

[haraldurkarlsson]

Greg,
I am having trouble seeing the difference between changing missing data to value vs imputation. Are they not the same? Can you explain the difference.
Thanks!
Great lessions by the way.

[markelov]

Could you please make a video on testing MCAR and, given its assumption of multivariate normality, talk specifically about what to do with factor variables or logicals?