Step-by-step explanation:
Part A: Linear Equation.
- One of the points is (0,15). This means 0,15 is the y intercept so b=15.
We can find the slope

So our equation is

Part B: Exponential Equation
We know that

B to the zero power is 1 so

This means a =15. Now let find b.


So the equation is

Answer:
9 2/3% (or 9.66666666666%)
Step-by-step explanation:
A percent is a ratio out of 100, as this answer is out of 100, the percent is just 9 2/3%.
Answer:
The confidence interval for 90% confidence would be narrower than the 95% confidence
Step-by-step explanation:
From the question we are told that
The sample size is n = 41
For a 95% confidence the level of significance is
and
the critical value of
is 
For a 90% confidence the level of significance is
and
the critical value of
is 
So we see with decreasing confidence level the critical value decrease
Now the margin of error is mathematically represented as
given that other values are constant and only
is varying we have that

Hence for reducing confidence level the margin of error will be reducing
The confidence interval is mathematically represented as

Now looking at the above formula and information that we have deduced so far we can infer that as the confidence level reduces , the critical value reduces, the margin of error reduces and the confidence interval becomes narrower
Answer:
Point Estimate for different between population means = - 0.99
Step-by-step explanation:
We are given data of two samples and we have to find the best point estimate of the true difference between two population means. Remember that in absence of data about population the best estimator is the sample data. So, we will find the means of both sample data and find the difference of that means. This difference between the means of sample data will be the best point estimate for the true difference between the population means.
Formula to calculate the mean is:

Mean of Sample 1:

Mean of Sample 2:

Therefore the best point estimate for difference between two population means would be = Mean of Sample 1 - Mean of Sample 2
= 128.55 - 129.54
= - 0.99