Answer correctly and read the questions corretly, take your time do not rush, this is all one quesiton if done correclty and organized I will write a very nice review about you! Stewart Fleishman specializes in the psychiatric aspects of symptom management in cancer patients. Pain, depression, and fatigue can appearas single symptoms, in conjunction with one other symptom, or all together in patients with cancer. You are interested in testing a new kind ofnutrition therapy for the treatment of the simultaneous clustering of depression and pain in cancer patients. The following scores represent thedecrease in symptom intensity (on a 10-point scale) following the new nutrition therapy.ScoresPatient Depression (X)ABсDE10Create a scatter plot of these scores on the grid. For each of the five (X, Y) pairs, drag the orange points (square symbol) in the upper-rightcorner of the diagram to the appropriate location on the grid.8002468102Pain (Y)0415246DEPRESSION8100Scores(?) Calculate the means and complete the following table by calculating the deviations from the means for X and Y, the squares of the deviations, andthe products of the deviations.ScoresXY2044618510 2DeviationsX - MX-2.002.00Y - My1.60Ży2.60Squared Deviations(X - MX)²4.004.00ZX(Y - My )²2.56Calculate the sum of the products and the sum of squares for X. SP =6.76Products(X - MX) (Y - My)-3.20Find the regression line for predicting Y given X. The slope of the regression line is5.20Calculate the standard error of the estimate. The standard error of the estimate isCalculate the Pearson correlation coefficient, the predicted variability, and the unpredicted variability. The Pearson correlation is r =The predicted variability is SS regression =The unpredicted variability is SSresidual =and SSX =and the Y intercept isSuppose you want to predict the pain score for a new patient. The only information given is that this new patient is similar to patients A throughE; therefore, your best guess for the new patient's level of pain is. The error associated with this guess (that is, the "standard"amount your guess will be away from the true value) isSuppose that now you are told the depression score for this new patient is 5.5. Now your best guess for the new patient's level of pain isThe error associated with this guess (that is, the "standard" amount your guess will be away from the true value) isFinally, suppose before estimating the regression equation, you first transform each of the original scores into a z-score. The regression equationyou estimate is:

Patient Depression (x) Pain (Y) A 2 0 B 4 4 C 6 1 D 8 5 E 10 2

Stewart Fleishman specializes in the psychiatric aspects of symptom management in cancer patients. Pain, depression, and fatigue can appear as single symptoms, in conjunction with one other symptom, or all together in patients with cancer. You are interested in testing a new kind of nutrition therapy for the treatment of the simultaneous clustering of depression and pain in cancer patients. The following scores represent the decrease in symptom intensity (on a 10-point scale) following the new nutrition therapy. Scores Patient Depression (X) Pain (Y) A 2 0 B 4 с 6 D 8 E 10 PAIN 10 Create a scatter plot of these scores on the grid. For each of the five (X, Y) pairs, drag the orange points (square symbol) in the upper-right corner of the diagram to the appropriate location on the grid. 8 8 2 of 4 2 1 5 2 сл DEPRESSION 00 10 Scores (?)

Stewart Fleishman specializes in the psychiatric aspects of symptom management in cancer patients. Pain, depression, and fatigue can appear as single symptoms, in conjunction with one other symptom, or all together in patients with cancer. You are interested in testing a new kind of nutrition therapy for the treatment of the simultaneous clustering of depression and pain in cancer patients. The following scores represent the decrease in symptom intensity (on a 10-point scale) following the new nutrition therapy. Scores Patient Depression (X) Pain (Y) A 2 0 B 4 с 6 D 8 E 10 PAIN 10 Create a scatter plot of these scores on the grid. For each of the five (X, Y) pairs, drag the orange points (square symbol) in the upper-right corner of the diagram to the appropriate location on the grid. 8 8 2 of 4 2 1 5 2 сл DEPRESSION 00 10 Scores (?)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Answer correctly and read the questions corretly, take your time do not rush, this is all one quesiton if done correclty and organized I will write a very nice review about you!

Stewart Fleishman specializes in the psychiatric aspects of symptom management in cancer patients. Pain, depression, and fatigue can appear
as single symptoms, in conjunction with one other symptom, or all together in patients with cancer. You are interested in testing a new kind of
nutrition therapy for the treatment of the simultaneous clustering of depression and pain in cancer patients. The following scores represent the
decrease in symptom intensity (on a 10-point scale) following the new nutrition therapy.
Scores
Patient Depression (X)
A
B
с
D
E
10
Create a scatter plot of these scores on the grid. For each of the five (X, Y) pairs, drag the orange points (square symbol) in the upper-right
corner of the diagram to the appropriate location on the grid.
8
0
0
2
4
6
8
10
2
Pain (Y)
0
4
1
5
2
4
6
DEPRESSION
8
10
0
Scores
(?)

Calculate the means and complete the following table by calculating the deviations from the means for X and Y, the squares of the deviations, and
the products of the deviations.
Scores
X
Y
2
0
4
4
6
1
8
5
10 2
Deviations
X - MX
-2.00
2.00
Y - My
1.60
Ży
2.60
Squared Deviations
(X - MX)²
4.00
4.00
ZX
(Y - My )²
2.56
Calculate the sum of the products and the sum of squares for X. SP =
6.76
Products
(X - MX) (Y - My)
-3.20
Find the regression line for predicting Y given X. The slope of the regression line is
5.20
Calculate the standard error of the estimate. The standard error of the estimate is
Calculate the Pearson correlation coefficient, the predicted variability, and the unpredicted variability. The Pearson correlation is r =
The predicted variability is SS regression =
The unpredicted variability is SSresidual =
and SSX =
and the Y intercept is
Suppose you want to predict the pain score for a new patient. The only information given is that this new patient is similar to patients A through
E; therefore, your best guess for the new patient's level of pain is
. The error associated with this guess (that is, the "standard"
amount your guess will be away from the true value) is
Suppose that now you are told the depression score for this new patient is 5.5. Now your best guess for the new patient's level of pain is
The error associated with this guess (that is, the "standard" amount your guess will be away from the true value) is
Finally, suppose before estimating the regression equation, you first transform each of the original scores into a z-score. The regression equation
you estimate is:

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Step 1: Given data:

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Step 2: Create a scatterplot for the data.

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Step 3: Calculate the means and complete the table:

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Step 4: Calculate the slope and intercept of the regression line:

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Step 5: Calculate the Pearson correlation coefficient, predicted and unpredicted variabilities:

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Step 6: Compute the standard error of the estimate:

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Step 7: Transform the given data into Z-scores:

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