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Mamagerial Economics Essay

618 words - 3 pages

University of Dhaka

Department
Of
Management Information Systems (MIS)

Term paper
On
Managerial Economics


Course Code: EMIS 505

Submitted to: Md. Abul Kashem

Submitted by: Nadia Shahrin Chandni

Student ID: 61323016044

Abstract

Verifying consistency of empirical data is the motto of this paper. Data of four different kinds of businesses –Soft drink, Refrigerator, Paint and Life Insurance Premium- have been tasted to establish and examine estimate function. SPSS has been used as based software for the study.

Introduction

Estimation is one of the core responsibilities of a manager. The aim of studying Managerial Economics, among other, is to equip managers with the economic tools that enable proper forecasting. Business environment has changed rapidly over the years, making decision making a tougher job and more complex one is well. To face the wrath of the complexities computer analysts have developed software, capable of ...view middle of the document...

135 + 5.272T + 20767H - 0.338R
Standard error of estimate, se = 5.338
Correction coefficient, r = 0.975

2. Refrigerator:

Summer is the hottest season for a refrigerator manufacturer but winter is cold. So, commission incentives are given to stimulate sales in the dull seasons.
Month | Sales×000$ | Promotion×000$ | Commission% | DI$ |
1 | 1000 | 10 | 20 | 2000 |
2 | 1200 | 10 | 18 | 5000 |
3 | 2000 | 15 | 18 | 5000 |
4 | 2500 | 20 | 18 | 5000 |
5 | 3000 | 25 | 18 | 5000 |
6 | 4000 | 25 | 18 | 3000 |
7 | 3500 | 20 | 18 | 5000 |
8 | 2500 | 10 | 18 | 5000 |
9 | 1000 | 5 | 20 | 5000 |
10 | 900 | 5 | 25 | 2000 |
11 | 900 | 5 | 25 | 2000 |
12 | 900 | 5 | 25 | 2000 |

Multiple regression equation:
y = -250.693 + 126.541P – 4.484C + 0.40D
Standard error of estimate, se = 544.925
Correction coefficient, r = 0.911
3. Paint:

Sherwin-Williams Co. sales data of ten regions are:
Region | Sales×1,000gallons | Promotion×1,000$ | Price$/gallon | DI×1,000$ |
1 | 160 | 150 | 15 | 19 |
2 | 220 | 160 | 13.5 | 17.5 |
3 | 140 | 50 | 16.5 | 14 |
4 | 190 | 190 | 14.5 | 21 |
5 | 130 | 90 | 17 | 15.5 |
6 | 160 | 60 | 16 | 14.5 |
7 | 200 | 140 | 13 | 21.5 |
8 | 150 | 110 | 18 | 18 |
9 | 210 | 200 | 12 | 18.5 |
10 | 190 | 100 | 15.5 | 20 |



Multiple regression equation:
Y = 310.245 + 0.008A – 12.202P + 2.677M
Standard error of estimate, se = 5.338
Correction coefficient, r = 0.975
4. Life Insurance Premium:

Executive Insurers, Inc.
Observation | Amount of Life Insurance×1,000$ | Annual Income×1,000$ | Age(Years) | Number of Children |
1 | 90 | 50 | 34 | 2 |
2 | 180 | 84 | 40 | 4 |
3 | 225 | 74 | 46 | 3 |
4 | 210 | 115 | 63 | 3 |
5 | 150 | 104 | 62 | 4 |
6 | 150 | 96 | 54 | 2 |
7 | 60 | 56 | 31 | 1 |
8 | 135 | 102 | 57 | 3 |
9 | 150 | 104 | 40 | 3 |
10 | 150 | 108 | 42 | 4 |
11 | 60 | 65 | 45 | 2 |
12 | 90 | 58 | 35 | 1 |



Multiple regression equation:
Y = -.023 + 0.391I+ 0.917A + 23.414C
Standard error of estimate, se = 43.595
Correction coefficient, r = 0.723

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