This video describes the differences between standard deviation and the standard error of the mean, and how they can be used to interpret data when the values are plotted as error bars on a graph.
Kevin Piers what I don't understand is where does the number 6.33 at 4:18 come from? Standard deviation of a list of red-colored numbers (averages from 12 experiments with Jack, on 3:40), that is of [100, 101, 99, 114, 103, 101, 95, 99, 95, 105, 100, 93], is not 6.33 but 5.25. I've checked with Python with numpy, by hand, and using online SD calculators. All give population SD as 5.25 and sample SD as 5.48.
it's because he has messed up a lot in this video. the s.d. of the first 5 trials listed for jack is 14.14 (not "16" as he claims later). and the SEM of *that* set is 6.32. so i assume that's what he was referring to with "6.33." ..as for the rest of the video, it's also not a very good explanation of a simple concept: i.e. that you can have quite variable data (say flipping a coin and calling heads "0" and tails "1") which could have a large s.d. no matter how many times you measure it (for the coin example it will approach 0.5 as the number of random flips grows), but nevertheless the uncertainty in the mean itself (represented by the SEM) will tend toward zero as you make more and more measurements, irrespective of how noisy those data are. the video could've used a better example (for instance, a person running anywhere is not a good example of independent data, as there could be trends in either direction -- faster or slower -- depending on the time between trials; thus these data are not even appropriately lumped together like this) and as you point out, he could've at least double checked his math before posting.
Piers Support Hello sir, I am having airborne dust concentrations data as PM10, PM2.5, PM 1 . These data was taken before and during dust producing work in a civil construction site. N=5 How can i compare these before and during operations data ? It seems that there is percent variation in dust concentrations in atmosphere between before and during operation data based on particle size. Before operation: PM 10 ( particle size less than 10 microns) is sharing 40% of total airborne dust, and PM 2.5 ( particle size less than 2. 5 micron) shares 10% of total airborne dust. During machine operation: PM 10 shares 60% and PM 2.5 10% only. It seems that PM 10 share is increased due to that machine operation? Which test is suitable for analysing these type similar data for discussion ? How to use statistics? Any comparison among these particle sizes? thank u.
No better explanation than this one. Can't thank you enough Dr. Piers. You're an exceptional instructor with the ability to clearly, precisely and simply explain very complex statistics topics. God bless you. Much appreciation from Uganda - East Africa.
Nice video thanks! Would you say in general that when a single person does the same test repeated times (person running a mile 5 times) you should show SEM but when you have a group of people that do the same test such as a team running a mile, then you show the SD?
Thank you so much, this is a wonderful tutorial. I am a TA for a data analysis course and was having the hardest time figuring out how to emphasize the difference between SD and SEM. You did it very clearly and simply!! You just saved my students from a very confusing lab explanation :)
Thank you very much for the video. I am a medical student. I needed a understanding of the difference between SD & SEM for community medicine. Your video helped me a lot...
I always explain it this way to students. SD is a measure of how big the spread is between samples. SEM is a measure how exact we know the average (or mean). It starts to get interesting when SD is relatively big. At that point one could argue how valid the test actually was. Because it's perfectly possible that the SD is very big (individual samples are widely spread) but SEM is quite small at the same time.
that's is really a simple access to the two complex concepts, thanks, that's really helpful for the psychology student without a math background to understand. you really knows what we are confusing in each steps.
Great video for SEM concept. Liked and subed. However, a question. SEM=SD/sqrt(n), here SD is directly from one sample set data? shouldn't it be the real statistic SD?
Thanks for the presentation on Std.Error of Mean. I calculated std.dev of the sample means and it came out to be 5.25. You noted SEM as 6.33, wondering wherefrom it came. Could you clarify
Hello. I was attempting to double check your work at 4:22 and I happen to find different results. Using Excel, the sample standard deviation for the set of averages is 5.483 and the population sample deviation is 5.250. Is this indeed a mistake or am I missing something?
