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X₁ SALES of similar package last year X₂ = DAYS on holiday X3 = ACCOM type B'B, Hotel and Self cater X4 = NUMBER of people booked for Ŷ = FAMP ( 1 = buying family package and 0 = not buying a package) 4.2. The data was modelled with a logistic regression function and SAS provided the maximum likelihood estimates, some of which are the following: b₁ = -0.073 and b3 = 0.05 Find the odds ratio for b₁ and b3 and give an interpretation of each.

X₁ SALES of similar package last year X₂ = DAYS on holiday X3 = ACCOM type B'B, Hotel and Self cater X4 = NUMBER of people booked for Ŷ = FAMP ( 1 = buying family package and 0 = not buying a package) 4.2. The data was modelled with a logistic regression function and SAS provided the maximum likelihood estimates, some of which are the following: b₁ = -0.073 and b3 = 0.05 Find the odds ratio for b₁ and b3 and give an interpretation of each.

MATLAB: An Introduction with Applications
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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4. A sales consultant realises that prospective buyers of holiday packages mostly want family packages. In a small study of 150 similar packages, he recorded the last year's sales, considering the duration of the holiday, number of people, and type of accommodation. A partial data set is given below. Table: Family package Famp (target) 0 1 1 0 Sales (in R1000.00) 13 4 3 8 Duration in days 15 20 10 10 1 Accomtype Number of people Bed 'n Breakfast Hotel Selfcater Hotel 7 5 10 12 The data of SALE was derived by using the following coding scheme X₁ = SALES of similar package last year X₂ = DAYS on holiday X3 = ACCOM type B'B, Hotel and Selfcat X4 = NUMBER of people booked for Ŷ = FAMP (1 = buying family package and 0 = not buying a package) 4.2. The data was modelled with a logistic regression function and SAS provided the maximum likelihood estimates, some of which are the following: b₁ = -0.073 and b3 = 0.05 Find the odds ratio for b₁ and b3 and give an interpretation of each.
Transcribed Image Text:4. A sales consultant realises that prospective buyers of holiday packages mostly want family packages. In a small study of 150 similar packages, he recorded the last year's sales, considering the duration of the holiday, number of people, and type of accommodation. A partial data set is given below. Table: Family package Famp (target) 0 1 1 0 Sales (in R1000.00) 13 4 3 8 Duration in days 15 20 10 10 1 Accomtype Number of people Bed 'n Breakfast Hotel Selfcater Hotel 7 5 10 12 The data of SALE was derived by using the following coding scheme X₁ = SALES of similar package last year X₂ = DAYS on holiday X3 = ACCOM type B'B, Hotel and Selfcat X4 = NUMBER of people booked for Ŷ = FAMP (1 = buying family package and 0 = not buying a package) 4.2. The data was modelled with a logistic regression function and SAS provided the maximum likelihood estimates, some of which are the following: b₁ = -0.073 and b3 = 0.05 Find the odds ratio for b₁ and b3 and give an interpretation of each.
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