At 3:02 to 3:27, 25 seconds, Dr. Grande explained the concept of standard error, and how it differs from standard deviation, which I could not find in five hours of googling the internet. This highlights the well-known problem in science writing, and Grande has defeated it with his own style. Sir, if I could give you 100 thumbs-up I would. Thank you.
😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮 Dr. Grande!!!!!!!!!!! I know you from 2023 True Crime/News Analysis!!! My mind is blown that you came up when I googled this topic😮😮😮😮😮😮😮!!!!!!!
I think the 1.96 has to do with the “n” sample size of 20. If you have a sample size of 25, then the 1.96 would be increased to 2 and if you wanted to increase the confidence interval of that same 25 sample size up to 99.7 confidence interval then you’d use a 3 instead of the 1.96
I am afraid you're incorrectly calculating 95% confidence intervals. 95% Confidence Interval = mean (-/+)1.96 * SD. You are effectively calculating Margins of Error = (-/+)1.96 SE * mean. They are useful especially for Bland Altman (measurement of agreement) Regarding the value of 1.96 if you plot random sample which should give you a graph of normal distribution and calculate SD and mean. You can mark those intervals on both ends and visually check if the 95% of your data lies within these limits.
Nice, simple explanation. Standard error of the mean is calculated by dividing the standard deviation by the square root of the sample size.
Now this is a concept that I am familiar with- calculating the range of error by dividing the standard deviation by the square root of the sample size
At 3:02 to 3:27, 25 seconds, Dr. Grande explained the concept of standard error, and how it differs from standard deviation, which I could not find in five hours of googling the internet. This highlights the well-known problem in science writing, and Grande has defeated it with his own style. Sir, if I could give you 100 thumbs-up I would. Thank you.
You're welcome - I'm so glad you found this explanation of the standard error to be helpful -
😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮😮
Dr. Grande!!!!!!!!!!!
I know you from 2023 True Crime/News Analysis!!!
My mind is blown that you came up when I googled this topic😮😮😮😮😮😮😮!!!!!!!
Hi Dr. Todd. Many thanks for such an informative and easy to understand tutorial.
Yet again, very clear on the steps and the reasoning behind the process. The clarification with Gregory below was also helpful.
Thanks so much for this Todd! Needed SEM for my anthropometry assessment measures.
You should write out the formulas in the information section. Makes it easier than hitting rewind a dozen times if we can't understand you.
This video is easy to follow- mostly because I am familiar with this concept.
where did u get 1.96 from sir?
Why SEM is high in some studies? What may cause that?
SEM and SE of mean are two different thing.
SEM - Standard Error of Measurement
SE of Mean - Standard Error of Mean
Isn't SEM the SD of the population divided by the square root of the sample size? Why are we using the SD of the sample in this case?
Thanks for your help!
You're welcome!
@@DrGrande
Mr Todd you explain nicely.
Thank you sir
Sir can you please explain how you got 1.96?
I think the 1.96 has to do with the “n” sample size of 20. If you have a sample size of 25, then the 1.96 would be increased to 2 and if you wanted to increase the confidence interval of that same 25 sample size up to 99.7 confidence interval then you’d use a 3 instead of the 1.96
Thank you very much!
You're welcome, thanks for watching -
I am afraid you're incorrectly calculating 95% confidence intervals.
95% Confidence Interval = mean (-/+)1.96 * SD.
You are effectively calculating Margins of Error = (-/+)1.96 SE * mean.
They are useful especially for Bland Altman (measurement of agreement)
Regarding the value of 1.96
if you plot random sample which should give you a graph of normal distribution and calculate SD and mean. You can mark those intervals on both ends and visually check if the 95% of your data lies within these limits.
+Peter R. The calculation (Mean +/- (SE * 1.96)) is for the 95% CI of the mean. It is to estimate the true population mean based on a sample.
Peter R. Can I ask where 1.96 comes from? what is it exactly?