Which of these statements are true if you need to make an inference about the mean of a population?
i. you must use a t test rather than a z-test unless you know the population standard deviation.
ii. if you do not know the population standard deviation, your sample must be a simple random sample from a normal population.
iii. sample sizes must be at least 30.

I. You must use a t test rather than a z-test unless you know the population standard deviation.

Correct when the population deviation is not known we can assume that the distribution follows a t distribution in order to do inferences about the population mean

II. If you do not know the population standard deviation, your sample must be a simple random sample from a normal population.

False is not required since we can use the t distribution when the sample size is not large enough and when the data is not perfectly Normal

III. Sample sizes must be at least 30.

True that ensure that the condition 2) would be satisfied.

Step-by-step explanation:

In order to make inferences about the population mean we need 4 important conditions:

1) Random: We need data from a random sample of size n out of the population of interest.

2) Normal: We need that the variable follows  a Normal distribution. Sometimes we just need   that the distribution would be symmetric and with a large sample.

3) Independent: We need that the population would be much larger than the sample (at least  20 or 30 times as large).

4) Standard Deviation: We need to have the population standard deviation.

Now if we analyze one by one the conditons we have:

I. You must use a t test rather than a z-test unless you know the population standard deviation.

Correct when the population deviation is not known we can assume that the distribution follows a t distribution in order to do inferences about the population mean

II. If you do not know the population standard deviation, your sample must be a simple random sample from a normal population.

False is not required since we can use the t distribution when the sample size is not large enough and when the data is not perfectly Normal

III. Sample sizes must be at least 30.

True that ensure that the condition 2) would be satisfied.

so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

mark brainliest!