01 - Sampling Distributions - Learn Statistical Sampling (Statistics Course)

This is just a few minutes of a complete course.
Get full lessons & more subjects at: www.MathTutorDVD.com.
In this lesson the student will learn the fundamentals of sampling distributions in statistics. We will discuss the normal distribution, skewed distributions, uniform distributions, and more.

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Thank you for this great video, learning to understand statistics and sampling variables, your teaching methods are the best!

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wow this has really helped me understand sampling Distribution, which was so alien before. Your explanation is so vivid.

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It's amazing how I quickly understood sampling distribution in just 24mins ...thanks

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THANK YOU! FOR YOUR EXCELLENT TEACHING METHOD! IT HAS GIVEN ME AN OPPORTUNITY TO LEARN ON STATISTICS!!

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Best way to teach sampling distribution is this.

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Action speaks louder than words Really the expressions helped a lot !

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I read sampling distribution over and over again and I got nothing. When I watched the video it was just like a magic wand of enlightenment thank you

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crystal clear concept. amazing teacher :)

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Mr Jason, you are the best of the best teacher. I never have a teacher whose explanation is so good, I have been struggling with sampling distributions, but after hearing your lesson it is so clear in mind now thank you :)

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[@jamesleem.d.7442]

At 15:43 you point out that Sample Size (n) is a different cat from Number of Samples Obtained. Thanks! A great number of the "online gurus" fail to do this, and all kinds of confusion results for students who are just starting out. Great lectures from you , by the way. Tip: The word "comprises" means "consists of" or "is made up of". "Comprise" is not interchangeable with "Compose". Illustration: Your lectures comprise a terrific set of lessons, tips, and illustrations.

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[@MsJeyran]

Can we calculate Sampling distribution for the samples that differ in size ? (f.e sample 1 n=23. sample 2 n=12 etc.)

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thank you so much sir.. to make that easy for as

[@thosgee747]

how many samples do I need in order to get a good sampling distribution? I am not asking about the size of the samples, but about the number of samples.

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Very informative. Thanks a lot.

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please where is the continuation of this

[@abubakarqahwe8754]

Thank you a lot, i just wanna ask you, when i wanna reject null hypotheses, do i use population or sample mean, i confused some text book examples? as you know sometimes errors has been occurred for instance if someone reject null hypothesis when it is true, so what is the difference between the mean obtained from sample and hypothesized mean?

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Thank you very for this video. Definitely a good one. I'd suggest drawing figures (e.g. of multiple samples of size n) which can be used to make it visual (rather than using hands). I believe it will make the explanation much better (one draw is sometimes better than 1000 words). Again, thank you for making it simple as it it really is simple

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Is it true that symmetry can be determined for all types of variables?

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What's the difference between a Sampling distribution and a sampling distribution of sampling mean? Thanks!

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Very good explanation

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Thank you Sir

[@gunhild1951]

When you're explaining the definition of sampling distribution I got confused a bit. Could you (or someone else here) clarify what's considered as sampling distribution. Is it specifically the calculated average or some other summary statistic from the different samples; sample A, sample B, sample C etecetera that is the sampling distribution OR are all the values from the different samples considered to be a part of the sampling distribution? I hope this make sense for you or any other that reads this.

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For better understanding, you should write your explanations for visual learners. I understood what you said, I wish you wrote it down while you were explaining. Besides that, great video.

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is there notes of these lecture?

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Thanks

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[@sayantanbiswas6038]

For a fixed population of size 'N' if we take a sample size of 'n'. Again we calculate the each possible sample mean then those sample means form a Sampling distribution of sample mean. Now the all possible sample means are discrete when these sample means will form a continuous distribution....???. Can anyone help me out...

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