Answer:
B) A one-sample t-test for population mean would be used.
Step-by-step explanation:
The complete question is shown in the image below.
The marketing executive is interested in comparing the mean number of sales of this year to that of previous year.
The marketing executive already has the value of mean from previous year and uses a sample to calculate the mean and standard deviation of sales for the current year.
Since, data is being collected for one sample only this limits us to chose between one sample test for mean. So now the possible options are one sample t-test for population mean and one sample t-test for population mean.
If we read the statement we can see that we have the value of sample mean and sample standard deviation. Value of population standard deviation is unknown. In cases where value of population standard deviation is not known and sample standard deviation is given, t-test is used.
Therefore, we can conclude that A one-sample t-test for population mean would be used.
Answer:
The answer is the first option
Step-by-step explanation:
516 is the dividend, 3 is the divisor, 172 would be the quotient.
3 goes into 5 once with a 2 remainder, that 2 turns into 21 because of the 1 in 516 which 3 goes into seven times with a remainder of zero turning into 6, which 3 goes into twice, making the quotient 172.
172 times 3 is 516
Hello using PEMDAS I came up with 63
division and multiplication first then add and subtract leaving you with 63
Answer:
a) 
b) r =-0.932
The % of variation is given by the determination coefficient given by 
and on this case 
, so then the % of variation explained by the linear model is 86.87%.
Step-by-step explanation:
Assuming the following dataset:
Monthly Sales (Y) Interest Rate (X)
22 9.2
20 7.6
10 10.4
45 5.3
Part a
And we want a linear model on this way y=mx+b, where m represent the slope and b the intercept. In order to find the slope we have this formula:
Where:
With these we can find the sums:
And the slope would be:
Nowe we can find the means for x and y like this:
And we can find the intercept using this:
So the line would be given by:
Part b
For this case we need to calculate the correlation coefficient given by:
![r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%28%5Csum%20xy%29-%28%5Csum%20x%29%28%5Csum%20y%29%7D%7B%5Csqrt%7B%5Bn%5Csum%20x%5E2%20-%28%5Csum%20x%29%5E2%5D%5Bn%5Csum%20y%5E2%20-%28%5Csum%20y%29%5E2%5D%7D%7D)
![r=\frac{4(696.9)-(32.5)(97)}{\sqrt{[4(278.65) -(32.5)^2][4(3009) -(97)^2]}}=-0.937](https://tex.z-dn.net/?f=r%3D%5Cfrac%7B4%28696.9%29-%2832.5%29%2897%29%7D%7B%5Csqrt%7B%5B4%28278.65%29%20-%2832.5%29%5E2%5D%5B4%283009%29%20-%2897%29%5E2%5D%7D%7D%3D-0.937)
So then the correlation coefficient would be r =-0.932
The % of variation is given by the determination coefficient given by and on this case , so then the % of variation explained by the linear model is 86.87%.
