4.48 Same observation, difference sample size: Suppose you conduct a hypothesis test based on a sample where the sample size is n = 50, and arrive at a p-value of 0.08. You then refer back to your notes and discover that you made a careless mistake, the sample size should have been n = 500. Will your p-value increase, decrease, or stay the same?

P-value is lesser in the case when n = 500.

Step-by-step explanation:

The formula for z-test statistic can be written as

here, μ = mean

σ= standard deviation, n= sample size, x= variable.

From the relation we can clearly observe that n is directly proportional to test statistic. Thus, as the value of n increases the corresponding test statistic value also increases.

We can also observe that as the test statistic's numerical value increases it is more likely to go into rejection region or in other words its P-value decreases.

Now, for  first case when our n is 50 we will have a relatively low chance of accurately representing the population compared to the case when n= 500. Therefore,  the P-value will be lesser in the case when n = 500.

a

step-by-step explanation:

when a number is between two straight lines it means the absolute value.

to find absolute value you need to know how many numbers is that number away from 0.

when finding absolute value the number will always come out positive

so absolute value of -3 is 3

absolute value of 3/2 is 3/2

absolute value of -2 is 2

absolute value of 3.5 is 3.5

absolute value of -1 is 1

now put these numbers in order:

a)   |-1|, |3/2|, |-2|, |-3|, |3.5|