Answer:
We can infer a cause-and-effect relationship because multiple variables were included.
Step-by-step explanation:
The multiple attributes for the divorced ones are
1) less physically active
2) an unhealthy weight,
3) smokers.
The attribute showing the % of the married is
1) death
So when we compare the two groups married and divorced we see different variables are involved in evaluating the percentage.
This shows a cause and effect involving multiple variables.
In cause and effect one variable is dependent and the other is independent.
The cause is the independent variable and effect is the dependent variable.
CAUSE EFFECT
Married Death
Divorced 1) less physically active
2) an unhealthy weight,
3) smokers.
Answer:
d. H0 : pˆ = .6, Ha: pˆ > .6
Step-by-step explanation:
Given that a minister claims that more than 60% of the adult population attends a religious service at least once a month.
Here the subject of interest about a proportion of adult population who attends a religious service at least once a month.
The claim is this proportion is greater than 60% and we want to check whether this claim is true.
Hence hypotheses would be for proportion only and not mean.
Since population proportion is to be checked we use p hat
Correct answer is
d. H0 : pˆ = .6, Ha: pˆ > .6
P=Q+20
or equivalently
P-Q=20
Edited 2018-03-18
Thank you Louli!
Answer:
Need the whole picture
Step-by-step explanation:
