The regression equation for the data given is y= -8.57 -2.31x
Step-by-step explanation:
The first step is to form a table as shown below;
x y xy x² y²
1 4 4 1 16
2 1 2 4 1
3 5 15 9 25
4 10 40 16 100
5 16 80 25 256
6 19 114 36 361
7 15 105 49 225
28 60 360 140 984 ------sum
A linear regression equation is in the form of y=A+Bx
where ;
x=independent variable
y=dependent variable
n=sample size/number of data points
A and B are constants that describe the y-intercept and the slope of the line
Calculating the constants;
A=(∑y)(∑x²) - (∑x)(∑xy) / n(∑x²) - (∑x)²
A=(60)(140) - (28)(360) / 7(140)-(28)²
A=8400 - 10080 /980-784
A= -1680/196
A= - 8.57
B= n(∑xy) - (∑x) (∑y) / n(∑x²) - (∑x)²
B= 7(360)-(28)(60) / 7(60) - (28)²
B=2520 - 1680 /420-784
B=840/-364
B= -2.31
y=A+Bx
y= -8.57 -2.31x
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Answer:
B
Step-by-step explanation:
So we have the formula:

And we want to solve it for r.
So, let's first divide both sides by π and h. This will cancel out the right side:

Now, take the square root of both sides:

And we're done!
Our answer is B.
I hope this helps!
Answer:
The critical value is T = 1.895.
The 90% confidence interval for the mean repair cost for the washers is between $48.159 and $72.761
Step-by-step explanation:
We have the standard deviation for the sample, so we use the t-distribution.
The first step to solve this problem is finding how many degrees of freedom, we have. This is the sample size subtracted by 1. So
df = 8 - 1 = 6
90% confidence interval
Now, we have to find a value of T, which is found looking at the t table, with 6 degrees of freedom(y-axis) and a confidence level of
. So we have T = 1.895, which is the critical value.
The margin of error is:

In which s is the standard deviation of the sample and n is the size of the sample.
The lower end of the interval is the sample mean subtracted by M. So it is 60.46 - 12.301 = $48.159
The upper end of the interval is the sample mean added to M. So it is 60.46 + 12.301 = $72.761
The 90% confidence interval for the mean repair cost for the washers is between $48.159 and $72.761