Answer:
- There is no significant evidence that p1 is different than p2 at 0.01 significance level.
- 99% confidence interval for p1-p2 is -0.171 ±0.237 that is (−0.408, 0.066)
Step-by-step explanation:
Let p1 be the proportion of the common attribute in population1
And p2 be the proportion of the same common attribute in population2
: p1-p2=0
: p1-p2≠0
Test statistic can be found using the equation:
where
- p1 is the sample proportion of the common attribute in population1 (
)
- p2 is the sample proportion of the common attribute in population2 (
)
- p is the pool proportion of p1 and p2 (
)
- n1 is the sample size of the people from population1 (30)
- n2 is the sample size of the people from population2 (1900)
Then 
≈ 2.03
p-value of the test statistic is 0.042>0.01, therefore we fail to reject the null hypothesis. There is no significant evidence that p1 is different than p2.
99% confidence interval estimate for p1-p2 can be calculated using the equation
p1-p2±
where
- z is the z-statistic for the 99% confidence (2.58)
Thus 99% confidence interval is
0.533-0.704±
≈ -0.171 ±0.237 that is (−0.408, 0.066)
18/30 simplifies into 6/10 which then is put in decimal form of 0.6
Answer:
x7-3 as number is multiplied by 7 then subtracted by 3
Answer:
l=(S-gn²/)i
Step-by-step explanation:
- S= il + gn²
- il=S-gn²
- l=(S-gn²/)i
The difference between causation and correlation is that, Causation is characterized by cause-and-effect while correlation establishes a probable relationship.
<h3>What is the difference between Causation and correlation?</h3>
While Causation is characterized by a situation in which an action certainly causes an outcome and hence, is described as a cause-and-effect relationship, Correlation on the other hand only establishes a relationship between the two events and doesn't necessarily ascertain the occurrence of the other event .
An example of two variables which may be correlated is; the height and weight of an individual in which case it is generally perceived that taller people are heavier.
Read more on correlation and causation;
brainly.com/question/964703
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