Solve your IGNOU Doubts

Question:

Describe one activity each for fostering the development of the following abilities in four year
old children.
(a) Pre-reading skills
(b) Creativity
(c) Fine motor skills
For each activity, mention its goals, material(s) required, if any and procedure to carry out the activity

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Question:

What are the motor abilities of a child in the age group of birth to 1 year of age?

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Question:

Explain the cephalocaudal and proximodistal directions of development.

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Question:

Identify an educational programme at school or college level, you are familiar with. Prepare a detailed plan for evaluating the same educational programme.

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Question:

Describe how learning experiences are organized and provided to learners in Open and Distance Learning System (ODLS)

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Question:

Describe the development of higher education during Post-independence period in India highlighting the role of University Grants Commission (UGC) in higher education.

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Question:

Gender and Health

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Question:

χ² test

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Question:

Environmental Health

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Question:

Random sampling

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Question:

Infectious Diseases

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Question:

Epidemic and Pandemic

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Question:

Discuss the impact of Globalisation on Human Health.

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Question:

Discuss the role played by Government of India in the management of COVID 19

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Question:

National Health Programmes in India

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Question:

Briefly discuss the core disciplines of Public Health.

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Question:

What is Epidemiology? Briefly examine various categories of Observational studies

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Question:

A clinical study was conducted on individuals with advanced stage of Hepatocellular Carcinoma to test three lines of Treatments: T1, T2 and T3. Thirthy-six patients with stage III Hepatocellular Carcinoma who agreed to take part in the experiment were randomly allocated one of three line of Treatments T1, T2 and T3. The primary outcome was mortality, and patients were monitored for up to 60 months (5 years) after recruitment. The data (in months) so obtained are given as follows:

Patient ID	Survival time	Outcome	Treatment	Patient ID	Survival time	Outcome	Treatment
ID001	14	Died	T3	ID019	50	Died	T1
ID002	27	Unknown	T1	ID020	54	Unknown	T3
ID003	37	Unknown	T3	ID021	57	Died	T2
ID004	44	Died	T1	ID022	60	Survived	T3
ID005	27	Died	T2	ID023	20	Died	T1
ID006	29	Died	T3	ID024	22	Unknown	T2
ID007	50	Died	T2	ID025	11	Unknown	T2
ID008	31	Died	T1	ID026	12	Unknown	T1
ID009	54	Died	T2	ID027	57	Unknown	T3
ID010	32	Died	T2	ID028	60	Survived	T3
ID011	32	Unknown	T2	ID029	44	Died	T1
ID012	60	Unknown	T1	ID030	47	Unknown	T2
ID013	2	Unknown	T2	ID031	32	Died	T2
ID014	42	Died	T3	ID032	34	Died	T1
ID015	42	Unknown	T2	ID033	17	Died	T2
ID016	60	Died	T3	ID034	6	Died	T1
ID017	60	Survived	T3	ID035	50	Unknown	T3
ID018	47	Died	T3	ID036	14	Unknown	T2

For this data,
(i) Construct Kaplan and Meier survival curves.
(ii) Test whether there is a significant difference between the survival distributions of the patients under all treatments at 5% level of significance.

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Question:

A hypothetical data of 40 patients on age (in years), weight (in kgs) and systolic blood pressure (in mm/hg) denoting 1 for high SBP and 0 for normal SBP are given in the following table:

S. No.	Age	Weight	SBP
1	52	60	0
2	56	68	1
3	51	54	0
4	63	74	1
5	54	62	0
6	51	67	0
7	51	66	0
8	54	65	0
9	59	71	1
10	51	89	1
11	56	72	1
12	55	72	1
13	46	57	0
14	42	54	0
15	52	63	0
16	65	67	1
17	50	67	0
18	42	53	0
19	50	68	1
20	39	55	0
21	47	48	0
22	42	45	0
23	45	57	0
24	56	83	1
25	49	63	0
26	56	94	1
27	55	87	1
28	53	67	0
29	65	70	1
30	44	70	0
31	48	54	0
32	61	79	1
33	45	85	0
34	63	98	1
35	49	78	0
36	65	80	1
37	60	70	1
38	53	98	1
39	41	53	0
40	50	70	1

For this data:

(i) Fit a multiple logistic regression model.

(ii) Test the significance of the individual model coefficients β₁ and β₂ at 5% level of significance.

(iii) Obtain the 95% confidence intervals for β₁ and β₂ .

(iv) Determine the Nagelkerke pseudo R-squared

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Question:

A researcher is interested to check the relationship between the serum creatinine (in mg/dL) with the weight (in kg) and gender (0 if female and 1 if male). The data were collected from the hospital records to examine the contribution of these variables to serum creatinine. A total of 40 patients were sampled and the data are shown in the following table:

S. No.	Serum Creatinine	Weight	Gender
1	0.7	46	1
2	1.3	65	1
3	1	59	1
4	1.5	84	0
5	1.7	91	1
6	1.5	78	1
7	1	53	0
8	0.7	49	1
9	0.5	42	0
10	1.6	87	0
11	1.1	53	1
12	0.8	54	0
13	1.3	65	1
14	1.1	61	1
15	1.3	71	0
16	1.3	71	0
17	1.2	68	0
18	1.3	65	1
19	1	55	1
20	1.2	66	0
21	1.1	55	1
22	0.9	55	0
23	0.9	62	0
24	1.1	65	0
25	0.8	54	0
26	0.5	45	0
27	0.6	45	0
28	1	62	0
29	0.5	40	0
30	0.9	58	0
31	1.3	65	1
32	1.1	58	1
33	1.4	67	1
34	0.8	42	1
35	1.6	81	1
36	1.8	92	1
37	1.5	80	0
38	1.7	91	1
39	0.8	55	0
40	0.5	33	0

(i) Prepare a scatter plot to get an idea about the relationship among the variables.
(ii) Fit a linear regression model and its related analysis at 1% level of significance.
(iii) Does the fitted regression model satisfy the linearity and normality assumptions?
(iv) Also, draw both fitted regression lines on the scatter plot.

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