Explanation:
The sample mean is not always equal to the population mean but if we take more and more number of samples from the population then the mean of the sample would become equal to the population mean.
The Central Limit Theorem states that we can have a normal distribution of sample means even if the original population doesn't follow normal distribution, But we have to take a lot of samples.
Suppose a population doesn't follow normal distribution and is very skewed then we can still have sampling distribution that is completely normal if we take a lot of samples.
Answer:
the answer is 2
Step-by-step explanation:
52÷2=26
26÷2=13
Answer:
16. Mst = 104°
17. The value of mPL is 31°
18. 129°
Step-by-step explanation:
Answer:
<u><em>14 pounds of strawberries and 42 pounds of peaches are sold</em></u>
Step-by-step explanation:
Suppose the pounds of strawberries sold are x and pounds of peaches sold are y. then
$182= x(1) + y(4)--------A
or 182= x(1) +3x(4)------- B
182=x+12x
182/13=x
x=14