a researcher selects a sample from a population with μ = 30 and uses the sample to evaluate the effect of a treatment. after treatment, the sample has a mean of m = 32 and a variance of s2 = 6. which of the following would definitely increase the likelihood of rejecting the null hypothesis?

question options:

a.
decrease the sample variance
b.
increase the sample mean
c.
increase the sample size
d.
all of the other options will increase the likelihood of rejecting the null hypothesis

Option b) Increase the sample mean

Step-by-step explanation:

Given that a researcher selects a sample from a population with μ = 30 and uses the sample to evaluate the effect of a treatment. After treatment, the sample has a mean of M = 32 and a variance of s2 = 6.

This is a paired test with test statistic

=mean diff/std error

Mean difference would increase if sample mean increases.

This would increase the test statistic

Or otherwise decrease in variance will increase the test statistic

Or Increase in sample size would also increase test statistic

Of all these the II option is definite in increasing the  likelihood of rejecting the null hypothesis because this would definitely increase the chances of rejecting H0.

Others may also have effect but not as much direct as sample mean difference.

Because variance and sample size have influence only upto square root of the difference.

days of the week

step-by-step explanation:

javier earned more money then kyle, so that won't always be a constant term, but the days of the week do not change so that term is always constant.

edit: i meant

javeir earned 56 dollors more than kyle so kyle and javier had 14w but javier made 56 dollors more so 14w plus 56 equals 70w so kyle has 14w

step-by-step explanation: hope i plz give me brainliest with the points so this is not constant cause it says last week so its clearly not every week