Yes, the sampling distribution is normally distributed because the population is normally distributed.
A sampling distribution is a chance distribution of a statistic obtained from a larger variety of samples drawn from a specific populace. The sampling distribution of a given population is the distribution of frequencies of a variety of various outcomes that would probable occur for a statistic of a populace.
A sampling distribution is a probability distribution of a statistic this is obtained via drawing a huge variety of samples from a particular populace. Researchers use sampling distributions so that you can simplify the technique of statistical inference.
Solution :
mean = μ40
standard deviation σ σ= 3
n = 10
μx = 40
σ x = σ√n = 3/√10 = 0.9487
μ x = 4σ\x = 0.9487
σx = 0.9487
Yes, the sampling distribution is normally distributed because the population is normally distributed.
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Let's use w to symbolize the weight of kittens. Given by the statement "each kitten weighs less than 3.5 ounces" we know that
1*w < 3.5
We can multiply both sides of the inequality by 7 to determine the total weights
7*(1*w) < 7*(3.5)
7*w < 24.5
Since there are 7 kittens, the combined weight of the kittens is 7w, therefore the above expression could be read as "The combined weight of the kittens is less than 24.5 ounces"
The division property of equality because you divide 20 by 5 to get the x value.
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The limits from either side are
The one-sided limits don't match, so the limit as 
does not exist.
The answer is C. 90 degrees.
This is because angle R is one of the four angles of a square.
I hope this helps.
