Report-3: Quantitative Analysis of Business and Economic Data to Inform Business Decisions
Name of the student:
Student ID number:
Name of the selected country: Switzerland
Name of the selected product: Apple
1. Executive summery
2. Introduction
3. Application of Analytical Techniques for Quantitative Analysis
(a) Application of basic statistical techniques
Table 1: GDP and sectoral contribution in (Switzerland) (in million dollars): 2000-2014
Year
GDP
HH Consumption
Export
Import
2000
271600
274821
264052
231024
2001
278629
280675
264012
233282
2002
301128
281606
258691
227865
2003
351983
282807
256174
228800
2004
393541
287938
280630
237795
2005
407536
292196
299010
261156
2006
429196
296524
317799
269448
2007
477408
303442
353915
285057
2008
551547
308032
367582
299052
2009
539528
311890
330912
287733
2010
581209
316992
428189
346155
2011
696279
319582
373421
311078
2012
665054
327903
391750
395932
2013
684535
335125
395932
330973
2014
702706
339200
456338
375510
Source: World Development Indicators 2016, the World Bank
(i) Descriptive statistics of data and interpretation
Formula Arithmetic Mean
(Talukder,2017a).
Mean: the average number
Median: the middle number
The median of GDP is :477408
Nariance
(Talukder,2017b).
Standard Deviation
(Talukder,2017c).
Table 2: Descriptive statistics of data from Table 1, 2000-2014
GDP
Household (HH) Consumption
Export (X)
Import (M)
Mean
488,791.9
303,915.5
335,893.8
288,057.3
Median
477,408
303,442
330,912
285,057
Variance
24132,338,818
433,484,305
4,278,386,061
3,010,423,206
Standard deviation
155,346
20,820
65,409
54,867
Source: Author's calculation based on table 1.
Interpretation of data to inform business decisions
(ii) Coefficient of variation (CV) and coefficient of correlation
Coefficient of variation (CV):
(Talukder,2017d).
Coefficient of correlation:
(Talukder,2017e).
Interpretation of data to inform business decisions
(b) Simple linear regression
Regression model: GDP as dependent variable and HH consumtiotion as independent variable
(Talukder,2017e).
(ii) Write formula and calculate the following terms and interprete results
Formula
The following is taken from Dr. Tulakder,2017f
Table 3: Simple linear regression results
(dependent variable: GDP, independent variable: HH consumpotion)
(1)
y-intercept (constant)
-1729,794
(2)
Regression coefficient (slope of regression line)
7.3
(3)
Random variable (error term)
33381.42
(4)
R-square
0.6
Source: Author's calculation based on table 1.
Draw a regression line:
Regression line
Source: Author's calculation based on table 1.
Interpretation of data to inform business decisions
(c) Multiple linear regression model
(i) Regression model: HH consumption as dependent variable and exports and imports as independent variables
(ii) Write formula and calculate the following terms and interprete results
Formula
The following is taken from Dr.Talukder 2017g
Table 4: multiple linear regression results
(dependent variable: HH comsumption, independent variables: exports and imports)
(1)
y-intercept (constant)
Exports
Imports
(2)
Regression coefficient 2 (exports)
146007
146007
(3)
Random variable (error term)
0.23
0.28
(3)
R-square
Interpretation of data to inform business decisions
4. Conclusion
5. References
6. Appendix
Talukder,D. (2017) 8220 Economics and Quantitative Analysis (week13).
[power point sliders] ICL Business School Auckland.
Talukder,D. (2017) 8220 Economics and Quantitative Analysis (week14).
[power point sliders] ICL Business School Auckland.
Talukder,D. (2017) 8220 Economics and Quantitative Analysis (week15).
[power point sliders] ICL Business School Auckland.
Lecturer: Dr. Dayal Talukder Page 3 of 3