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Chebyshev's Rule is valid for k > 1, we can find the valuesuch that at least this proportion of the data will fall within 1.1standard deviations of the mean...

Question

Chebyshev's Rule is valid for k > 1, we can find the valuesuch that at least this proportion of the data will fall within 1.1standard deviations of the mean even if the data is not known tocome fro a bell-shaped distribution. true or false

Chebyshev's Rule is valid for k > 1, we can find the value such that at least this proportion of the data will fall within 1.1 standard deviations of the mean even if the data is not known to come fro a bell-shaped distribution. true or false



Answers

True or False: A confidence interval for a population standard deviation is of the form point estimate $\pm$ margin of error.

Welcome to this lesson in this lesson, You've been a sexual false question and it's about drawing a confidence interval by the variance or standard deviation of population. So, if the question is if you're drawing this confidence interval about last standardization of variants is either the population they're drawing from has a distribution, that is normal. All the sample size is very huge. And these are the, according to the question. These are the precondition for drawing a confidence interval about variance and standard deviation. So that is false. You can have some kind of distribution that is fairly normal, probably skewed a little to the writer, uh the left, but can have a very you can have a confidence interval that would greatly represent the data that you are. If you are drawing from. Okay, the other way, you can also have sample size, there is no great bad control confidence interval about the variance and I quickly represent the values that you have you have based on to draw from. All right, So thanks for the time, this is the end of the lesson.

Exactly the statement is through here because the limped off the confidence interval for the mean is dependent on the population standard deviation. And if this population standard deviation is relatively a small, uh, then we know that the confidence in terrible will be relatively smaller also.

The answer for this question will be true. Now I will explain why it is true So the condition, the condition of normality, the condition of normality for the response variable for response variable age essential it is essential for at least is Squire for Lyft The Squires Regulation analyzes. So in this way, the answer for this problem is covered. That is true.

So if the P value in a statistical test is greater than the level of significance for the test, We actually failed to reject anil hypothesis, meaning if my alpha value is 0.05, and if my p value Comes out to be let's say 0.06, my p value will be greater than alpha, and hence I will fail to reject final hypothesis. Why is this? What exactly is fee value? P value is the probability that I am observing this by chance, right? P value means the value is basically the chance of getting something that you already have or something rarer than that. Okay, so I will fail to reject minor hypothesis, fail to reject my nail hypothesis. H not? Oh!


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