Answer:
For 25, the answer is C
Step-by-step explanation:
How I got the answer for 25 is:
To find the mean absolute deviation of the data, start by finding the mean of the data set.
How you do this is first you need to find the sum of the data values, (add all the numbers together) and divide the sum by the number of data values.(and divide that number by how many numbers you added together in the first place)
In this case, we'd be adding 44 + 39 + 47 + 38 + 38 + 41 + 40, and that equals 287. Now we'll divide 287 by how many numbers we added together, which is 7 numbers. 287 ÷ 7 = 41. That's the mean of the data set.
Next, we'll find the absolute deviation of the mean. How we do this is, we find how far away all the numbers are from 41.
44 is 3 away from 41
39 is 2 away from 41
47 is 6 away from 41
38 is 3 away from 41
41 is 0 away from 41
40 is 1 away from 41
So now, we add all of the distances together (3, 2, 6, 3, 0, and 1), and that equals 15! Now we do 15 ÷ 6, which is 2.5 and the reason we're dividing by 6 is because we're dividing by the number of distances we added together. Now, if you look on your worksheet, the closest answer to 2.5 is C, (2.6) so I'd chose that as the correct answer. I hope that helped!
Answer:
This statement is true because if F statistics is significant, then the entire multiple regression model is useful for the prediction of y.
Step-by-step explanation:
Solution:
In a multiple linear regression analysis, the statistical model utility is determined by the value of R2 and ∂2, while the Global F test p-value determines the practical model.
This statement is true because if F statistics is significant, then the entire multiple regression model is useful for the prediction of y.
The F test is a statistical test that is very flexible. F test can evaluate multiple model terms.
The F test indicates whether a linear regression model provides a better fit to data than a model that contains no independent variable.
The F test for overall significance has two hypotheses:
1- Null hypothesis:
The fit of the intercept only model and your model are equal.
2- Alternative hypothesis:
The fit of the intercept-only model is significantly reduced compared to your model.
Compare p-value for the F test,
If the p-value is less than the significance level, the sample data provide sufficient evidence that the regression model fits the data better with no independent variable.
20/36 reduced is 5/9. hope this helped! :)
Answer:
SAS, SSS, AAA
Step-by-step explanation:
Because Im bored X D
When you multiply powers, they add, and when you divide them they subtract.
So I would first add the 2^a + 2^b +2^c to get 2^(a+b+c)
Then, divide by 2^(a+b). Because when you divide powers they subtract, you will be taking away the (a+b) from the (a+b+c) and you will be left with c on its own.
The answer is 2^c
