Here is the graph, it's just a line.
Answer:
Step-by-step explanation:
Hello!
Suppose that the objective of the experiment is to test if a certain treatment modifies the mean of the population of interest.
If for example, the treatment is "new fertilizer" and the population of interest is "yield of wheat crops"
Then you'd expect that using the new fertilizer will at least modify the average yield of the wheat crops.
The hypotheses will be then
H₀: μ = μ₀
H₁: μ ≠ μ₀
Where μ₀ represents the known average yield of wheat crops. (is a value, for this exercise purpose there is no need to know it)
We know that the treatment modifies the population mean, i.e. the null hypothesis is false.
The sample we took to test whether or nor the new fertilizer works conducts us to believe, it does not affect, in other words, we fail to reject the null hypothesis.
Then we are in a situation where we failed to reject a false null hypothesis, this situation is known as <em><u>Type II error</u></em>.
I hope this helps!
Answer:
2
Step-by-step explanation:
If A = (2, 3) then a dilation of scale factor 2 means that the x and y coordinates are multiplied by 2, so x = 2 x 2 = 4 and y = 3 x 2 = 6, so A' = (4, 6)
Answer: 1: 45
Hope this helps!
<u>Answer:</u>
243 students are involved in either sports or music whereas 100 are not
involved in either of it.
<u>Step-by-step explanation:</u>
No. of students who are in music = 115
No. of students who are in sports = 197
No. of students who are in both activities = 69
So, no. of students who are involved either in sports or music,
= (115 + 197 - 69)
=243
So, no. of students who are not involved in either sports or music,
= (343 - 243)
=100
