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IGNOU MST 17 SOLVED ASSIGNMENT

IGNOU MST 17 SOLVED ASSIGNMENT


IGNOU MST 17 Solved Assignment 2025
Rs. 400
Rs. 205

IGNOU MST 17 SOLVED ASSIGNMENT

Rs. 400
Rs. 205

Last Date of Submission of IGNOU MST-017 (MSCAST) 2025 Assignment is for January 2025 Session: 30th September, 2025 (for December 2025 Term End Exam).
Semester Wise
January 2025 Session:
30th March, 2025 (for June 2025 Term End Exam).
July 2025 Session: 30th September, 2025 (for December 2025 Term End Exam).

Title NameIGNOU MST 17 SOLVED ASSIGNMENT
TypeSoft Copy (E-Assignment) .pdf
UniversityIGNOU
DegreeMASTER DEGREE PROGRAMMES
Course CodeMSCAST
Course NameM.Sc. (Applied Statistics)
Subject CodeMST 17
Subject NameApplied Regression Analysis
Year2025
Session
LanguageEnglish Medium
Assignment CodeMST-017/Assignmentt-1//2025
Product DescriptionAssignment of MSCAST (M.Sc. (Applied Statistics)) 2025. Latest MST 017 2025 Solved Assignment Solutions
Last Date of IGNOU Assignment Submission
Last Date of Submission of IGNOU MST-017 (MSCAST) 2025 Assignment is for January 2025 Session: 30th September, 2025 (for December 2025 Term End Exam).
Semester Wise
January 2025 Session:
30th March, 2025 (for June 2025 Term End Exam).
July 2025 Session: 30th September, 2025 (for December 2025 Term End Exam).

Rs. 400
Rs. 205
Questions Included in this Help Book

Ques 1.

State whether the following statements are true or false and also give the reason in support of your answer.

(i) We define three indicator variables for an explanatory variable with three categories.

(ii) If the coefficient of determination is 0.833, the number of observations and explanatory variables are 12 and 3, respectively, then the Adjusted R² will be 0.84.

(iii) For a simple regression model fitted on 15 observations, if we have h₁ = 0.37, then it is an indication to trace the leverage point in the regression model.

(iv) In a regression model equation is not rejected, then the variable X₁ will remain in the model.

(v) The logit link function is log [-log(1-π)].

Ques 2.

Write a short note on the problem of multicollinearity and autocorrelation.

Ques 3.

Suppose a researcher wants to evaluate the effect of cholesterol on the blood pressure. The following data on serum cholesterol (in mg/dL) and systolic blood pressure (in mm/Hg) were obtained for 15 patients to explore the relationship between cholesterol and blood pressure:

S. No . Cholesterol (mg/dL) SBP (mm/Hg)
1 300 150
2 410 270
3 380 210
4 530 310
5 570 350
6 490 310
7 340 210
8 320 150
9 280 110
10 550 320
11 340 220
12 350 170
13 410 260
14 390 230
15 450 270

(i) Fit a linear regression model using the method of least squares.

(ii) Construct the normal probability plot for the regression model fitted on serum cholesterol and systolic blood pressure.

(iii) Test the significance of the fitted regression model.

Ques 4.

Explain the assumptions underlying the multiple linear regression model.

Ques 5.

For the data given in Question 2(b), obtain the followings:

(i) Diagonal of the hat matrix. Also, check the leverage points, if any.

(ii) Cook’s Distances. Also, verify the influence points, if any.

Ques 6.

A company conducted a study on its employees to see the relationship of several variables with an employee’s IQ. For this purpose, fifteen employees were selected, and an IQ test and five different personality tests were given to them. Each employee’s IQ was recorded along with scores on five tests. The data are shown in the following table

Employee Test 1 Test 1 Test 3 Test 4 Test 5 IQ
1 83 80 78 77 67 99
2 73 85 67 80 63 92
3 81 80 71 81 68 94
4 96 86 82 83 56 99
5 84 73 75 75 68 94
6 72 74 71 67 59 79
7 84 79 84 84 69 97
8 54 86 61 69 53 92
9 86 85 79 78 76 94
10 42 71 60 80 56 86
11 83 72 72 78 74 98
12 63 86 65 85 56 83
13 69 76 64 85 61 98
14 81 84 65 85 64 96

Determine the most appropriate regression model for the employee’s IQ using a stepwise approach at a 5 % level of significance and interpret the results. Does the final regression model satisfy the linearity and normality assumptions?

Ques 7.

The following data on the diagnosis of coronary heart disease (where 0 indicates absence and 1 indicates presence), serum cholesterol (in mg/dl), and weight (in kg) were obtained for 80 patients to explore the relationship of coronary heart disease with cholesterol and weight:

S. No. Serum Cholesterol (mg/dl) Weight (kg) Number of Patients having CHD Total Number of Patients
1 420 60 10 20
2 450 68 15 30
3 400 54 4 15
4 510 74 2 10
5 480 62 1 5

(i) Fit a multiple logistic model for the dependence of coronary heart disease on the  average serum cholesterol and weight considering equation as the initial values of the parameters (solve only for one Iteration).

(ii) Test the significance of the fitted model using the Hosmer-Lemeshow test at 5% level of significance.

Ques 8.

State whether the following statements are true or false and also give the reason in support of your answer.

(i) We define three indicator variables for an explanatory variable with three categories.

(ii) If the coefficient of determination is 0.833, the number of observations and explanatory variables are 12 and 3, respectively, then the Adjusted R² will be 0.84.

(iii) For a simple regression model fitted on 15 observations, if we have h₁ = 0.37, then it is an indication to trace the leverage point in the regression model.

(iv) In a regression model equation is not rejected, then the variable X₁ will remain in the model.

(v) The logit link function is log [-log(1-π)].

Ques 9.

Write a short note on the problem of multicollinearity and autocorrelation.

Ques 10.

Suppose a researcher wants to evaluate the effect of cholesterol on the blood pressure. The following data on serum cholesterol (in mg/dL) and systolic blood pressure (in mm/Hg) were obtained for 15 patients to explore the relationship between cholesterol and blood pressure:

S. No . Cholesterol (mg/dL) SBP (mm/Hg)
1 300 150
2 410 270
3 380 210
4 530 310
5 570 350
6 490 310
7 340 210
8 320 150
9 280 110
10 550 320
11 340 220
12 350 170
13 410 260
14 390 230
15 450 270

(i) Fit a linear regression model using the method of least squares.

(ii) Construct the normal probability plot for the regression model fitted on serum cholesterol and systolic blood pressure.

(iii) Test the significance of the fitted regression model.

Ques 11.

Explain the assumptions underlying the multiple linear regression model.

Ques 12.

For the data given in Question 2(b), obtain the followings:

(i) Diagonal of the hat matrix. Also, check the leverage points, if any.

(ii) Cook’s Distances. Also, verify the influence points, if any.

Ques 13.

A company conducted a study on its employees to see the relationship of several variables with an employee’s IQ. For this purpose, fifteen employees were selected, and an IQ test and five different personality tests were given to them. Each employee’s IQ was recorded along with scores on five tests. The data are shown in the following table

Employee Test 1 Test 1 Test 3 Test 4 Test 5 IQ
1 83 80 78 77 67 99
2 73 85 67 80 63 92
3 81 80 71 81 68 94
4 96 86 82 83 56 99
5 84 73 75 75 68 94
6 72 74 71 67 59 79
7 84 79 84 84 69 97
8 54 86 61 69 53 92
9 86 85 79 78 76 94
10 42 71 60 80 56 86
11 83 72 72 78 74 98
12 63 86 65 85 56 83
13 69 76 64 85 61 98
14 81 84 65 85 64 96

Determine the most appropriate regression model for the employee’s IQ using a stepwise approach at a 5 % level of significance and interpret the results. Does the final regression model satisfy the linearity and normality assumptions?

Ques 14.

The following data on the diagnosis of coronary heart disease (where 0 indicates absence and 1 indicates presence), serum cholesterol (in mg/dl), and weight (in kg) were obtained for 80 patients to explore the relationship of coronary heart disease with cholesterol and weight:

S. No. Serum Cholesterol (mg/dl) Weight (kg) Number of Patients having CHD Total Number of Patients
1 420 60 10 20
2 450 68 15 30
3 400 54 4 15
4 510 74 2 10
5 480 62 1 5

(i) Fit a multiple logistic model for the dependence of coronary heart disease on the  average serum cholesterol and weight considering equation as the initial values of the parameters (solve only for one Iteration).

(ii) Test the significance of the fitted model using the Hosmer-Lemeshow test at 5% level of significance.

Rs. 400
Rs. 205
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IGNOU MSCAST Assignments Jan - July 2025 - IGNOU University has uploaded its current session Assignment of the MSCAST Programme for the session year 2025. Students of the MSCAST Programme can now download Assignment questions from this page. Candidates have to compulsory download those assignments to get a permit of attending the Term End Exam of the IGNOU MSCAST Programme.

Download a PDF soft copy of IGNOU MST 17 Applied Regression Analysis MSCAST Latest Solved Assignment for Session January 2025 - December 2025 in English Language.

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If you’ve arrived at this page, you’re looking for a free PDF download of the IGNOU MSCAST Solved Assignment 2025. MSCAST is for M.Sc. (Applied Statistics).

IGNOU solved assignments are a set of questions or tasks that students must complete and submit to their respective study centers. The solved assignments are provided by IGNOU Academy and must be completed by the students themselves.

Course Name M.Sc. (Applied Statistics)
Course Code MSCAST
Programm MASTER DEGREE PROGRAMMES Courses
Language English

 

 

 
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