Explain the assumptions underlying multiple linear regression model.

Question

08 Mar 2024

Answer :

Word Count : 356

In Biostatistics-II, understanding the assumptions underlying multiple linear regression models is crucial for accurate analysis and interpretation of data. These assumptions provide the foundation for the validity of the model and the reliability of its results. Here are the key assumptions:

1. Linearity: The relationship between the dependent variable (Y) and each independent variable (X) is linear. This means __________ ________ ______ ___ _______ _____ _____ ____ ___ _______ _____ _____.
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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

Workout (in minutes)	Severity of diabetes status
Workout (in minutes)	Low	Moderate	High
0 −15	06	27	19
15 to 30	08	38	17
30 to 45	21	45	33
≥ 45	14	18	06

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

Disease	Test result		Total
Disease	+	-	Total
Present	170	30	200
Absent	20	280	300

	Lung Cancer	No Lung Cancer	Totel
Smokers	100	1220	1320
Non-smokers	50	2260	2310