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for a normal-shaped distribution with n=50 and siqma =8 : a- what proportion of the scores have values between 46 and 54? b- for samples of n= 4, what means have values what proportion of the sample mean have values between 46 and 54? c- for samples of n= 16, what means have values what proportion of the sample mean have values between 46 and 54?
1. In a random sample of 200 persons of a town, 120 are found to be tea drinkers. In a random sample of 500 persons of another town, 240 are found to be tea drinkers. Is the proportion of tea drinkers in the two towns equal? Use 0.01 level of significance.
The answer depends on what population characteristic A measures: whether it is mean, variance, standard deviation, proportion etc. It also depends on the sampling distribution of A.
A half.
i dont no the answer
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it is the test one tail
i THINK IT IS .05
I dont really konw im doing this for the pnits srry
for a normal-shaped distribution with n=50 and siqma =8 : a- what proportion of the scores have values between 46 and 54? b- for samples of n= 4, what means have values what proportion of the sample mean have values between 46 and 54? c- for samples of n= 16, what means have values what proportion of the sample mean have values between 46 and 54?
The distribution of the sample mean is bell-shaped or is a normal distribution.
The distribution of sample means will not be normal if the number of samples does not reach 30.
The sampling proportion may be used to scale up the results from a sample to that of the population. It is also used for designing stratified sampling.
p-hat is the 'proportion in your sample.' It may be given as a percentage, a proportion or you will have to figure it out as a fraction (proportion).
An F-statistic is a measure that is calculated from a sample. It is a ratio of two lots of sums of squares of Normal variates. The sampling distribution of this ratio follows the F distribution. The F-statistic is used to test whether the variances of two samples, or a sample and population, are the same. It is also used in the analysis of variance (ANOVA) to determine what proportion of the variance can be "explained" by regression.