Answer:
True
Step-by-step explanation:
Type I and Type II are not independent of each other - as one increases, the other decreases.
However, increases in N cause both to decrease, since sampling error is reduced.
A small sample size might lead to frequent Type II errors, i.e. it could be that your (alternative) hypotheses are right, but because your sample is so small, you fail to reject the null even though you should.
Can we get a picture please
Answer:
1
Step-by-step explanation:
The y intercept is when x =0
We need to use the second equation
-x+1 since -2 < 0 <3
0+1
The y intercept is 1
145%
200/200: 100%
90/200= 45%