Answer:
It may be D, correct me if i'm wrong.
Step-by-step explanation:
We already know that the majority of students will go to a college based on somebody else going to that college. With that in mind, we can draw a cause-and-effect conclusion summarizing why they want to choose that college (Because there friend) and the effect as there friend goes to that college.
Answer:
Ok, so we can express the boys as another letter. just express them as the letter B for boys.
Step-by-step explanation:
I really don't know why.
Answer:
d. H0: melanoma mortality rate is not linearly related to latitude
Ha: melanoma mortality rate is linearly related to latitude
Step-by-step explanation:
The linear regression equation is
y=α+βx where α=intercept and β=slope.
β=slope demonstrates the change in dependent variable due to unit change in independent variable.
If the slope is zero then we can say that Y and X are not linearly related.
Thus, the hypothesis for testing significance of linear relationship two variables can be written as
Null hypothesis: The two variables are not linearly related i.e. β=0
Alternative hypothesis : The two variables are linearly related i.e. β≠0.
Thus, in the given scenario the hypothesis are
H0: melanoma mortality rate is not linearly related to latitude
Ha: melanoma mortality rate is linearly related to latitude.
Answer:
top right
Step-by-step explanation:
if you solve an equation for a triangle using this method you'll get this result
Answer:
15 and 20
Step-by-step explanation:
