. Develop a linear-regression-based forecasting model to predict costs. b. Predict costs when patient days are 520, 530, 540, and 550.
. Develop a linear-regression-based forecasting model to predict costs. b. Predict costs when patient days are 520, 530, 540, and 550.
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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a. Develop a linear-regression-based forecasting model to predict costs.
b. Predict costs when patient days are 520, 530, 540, and 550.

Transcribed Image Text:TABLE EX 2.6
Period
Cost
Patient Days
October: Year 1
32,996
516
November: Year 1
34,242
530
December: Year 1
27,825
528
January: Year 2
February: Year 2
29,807
517
28,692
500
March: Year 2
34,449
514
April: Year 2
33,335
515
May: Year 2
38,217
509
June: Year 2
36,690
524
July: Year 2
35,303
524
539
August: Year 2
September: Year 2
33,780
32,843
551
October: Year 2
37,781
543
November: Year 2
27,716
528
December: Year 2
31,876
531
542
January: Year 3
February: Year 3
31,463
29,829
558

Transcribed Image Text:2.6 A hospital pharmacy would like to develop a budget for allergy medications that is based
on patient days. Cost and patient days data were collected over a 17-month period as
shown in Table EX 2.6.
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