Answer:
The first question answer is Fred. The second one is 1/7. Sorry that is all i know.
Step-by-step explanation:
Explanation:
Lets interpret Z with M trials. First we have M trials, each trial can be a success or not. The number of success is called N. Each trial that is a success becomes a trial, and if it is a success it becomes a success for Z. Thus, in order for a trial to be successful, it needs first to be successful for the random variable N (and it is with probability q), and given that, it should be a success among the N trials of the original definition of Z (with probability p).
This gives us that each trial has probability pq of being successful. Note that this probability is pq independently of the results of the other trials, because the results of the trials of both N and the original definition of Z are independent. This shows us that Z is the total amount of success within M independent trials of an experiment with pq probability of success in each one. Therefore, Z has Binomial distribution with parameters pq and M.
Step-by-step explanation:
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Answer:
The most appropriate inference procedure for the investigation is;
a. A linear regression t-interval for the slope
Step-by-step explanation:
Given that the slope of an horizontal line is zero, we have that there is no change in the y (dependent) variable when there is a change in the x-variable, therefore, it is important to find the true relationship between the two variables, 'x', and 'y'
The confidence interval of the slope is calculated and analyzed to determine if it excludes or includes, 0, such that, if the confidence interval exclude 0, then, it is unlikely that the slope is 0, therefore, there the relationship between the variables, 'x', and 'y' is significant
Therefore, a linear regression t-interval for the slope is most appropriate.
Answer:
y = 2x + 16
Step-by-step explanation:
slope is parallel and equal to y = 2x + 6
y intercept = 16
