Quantitative Skills for Business: Analyzing Economic Variables

Desklib provides solved assignments and past papers to help students succeed.

QUANTITATIVE SKILLS FOR
BUSINESS
1

Table of Contents
Introduction....................................................................................................................................3
Description of data.........................................................................................................................3
Analysis...........................................................................................................................................4
Conclusion......................................................................................................................................9
References.....................................................................................................................................10
2

Introduction
The given report focuses primarily on the two economic variables. One of the variable is micro
economic variable and the other variable is macro-economic variable. Accordingly, the
dependent variable has been taken to be ‘other financial corporations and money market funds’.
The unit of dependent variable is gross value added (IMA) which has been denominated by
million dollars. On the other hand, consumer price index is the independent variable. Different
markets have varied significant impact. Some major statistical tools have been used in this
report.
Description of data
Both the variables have different units. One of the variable is in %. Another variable is money
market funds which is in $.This will facilitate a better comparison between the two given
variables which will help to form a better conclusion or interpretation.
Year Prices, Consumer Price Index,
All items, Percentage change,
Corresponding period previous
year, Percent
Other financial corporations
and money market funds; gross
value added (IMA)
2009 -0.36 439982
2010 1.64 509855
2011 3.16 551153
2012 2.07 645460
2013 1.46 630364
2014 1.62 677332
2015 0.12 651780
2016 1.26 665283
2017 2.13 703903
For the purpose of comparison of two variables, data of last 9 years has been taken into
consideration. This will help to properly analyses the data so that proper and reasonable
conclusion can be derived therefrom. All the other variables has been assumed to be constant so
that correct extent and nature of relationship can be determined (Harding, et. al., 2014).
3

Analysis
Descriptive statistics
Prices, Consumer Price Index, All items, Percentage change,
Corresponding period previous year, Percent
Mean 1.46
Standard Error 0.35
Median 1.62
Mode #N/A
Standard Deviation 1.06
Sample Variance 1.11
Kurtosis 0.35
Skewness -0.39
Range 3.52
Minimum -0.36
Maximum 3.16
Sum 13.10
Count 9.00
Since the range of the two variables are totally different, there has been a significant difference
between all the measures of central tendency. All the statistical tools are commonly part of the
descriptive statistics. The number of both the variables are same in both the cases. It will be
easier if the relationship between these two related variables have been explained in the graphical
form. Furthermore, the skewness of the both the variables are negative. On the other hand,
kurtosis of the both the variables are almost negligible or almost equal to 0. In simpler terms,
kurtosis of money market funds is 0 and in the same manner, kurtosis of CPI is 0.35. Thus, it can
be said that both the variables move in the same direction with a change in the any of the
variable operating or functioning in the market (Waltenburg, 2012).
Descriptive statistics
Other financial corporations and money market funds; gross value
added (IMA)
Mean 608345.78
Standard Error 29391.69
Median 645460.00
Mode #N/A
Standard Deviation 88175.07
4

Sample Variance 7774842114.44
Kurtosis 0.00
Skewness -1.03
Range 263921.00
Minimum 439982.00
Maximum 703903.00
Sum 5475112.00
Count 9.00
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
-100000
0
100000
200000
300000
400000
500000
600000
700000
800000
f(x) = 0.0381666666666667 x − 75.3739444444445
R² = 0.00980188507615154
Graph of CPI and Money market funds
Prices, Consumer Price Index, All items, Percentage change, Corresponding period previous year, PercentLinear (Prices, Consumer Price Index, All items, Percentage change, Corresponding period previous year, Percent)Linear (Prices, Consumer Price Index, All items, Percentage change, Corresponding period previous year, Percent)Linear (Prices, Consumer Price Index, All items, Percentage change, Corresponding period previous year, Percent)Other financial corporations and money market funds; gross value added (IMA)
The above graph explains the relationship that exists between the given two economic variables.
Since, the consumer price index tends to create different impact on varied nations, for the sake of
convenience particularly, United States has been taken.
SUMMARY
OUTPUT
Regression
Statistics
Multiple R 0.29
R Square 0.09
Adjusted R -0.04
5

Square
Standard
Error
90072
.69
Observations 9.00
ANOVA
df SS MS F Signific
ance F
Regression 1.00 540711551
4.44
54071155
14.44
0.67 0.44
Residual 7.00 567916214
01.11
81130887
71.59
Total 8.00 621987369
15.56
Coeffi
cients
Standard
Error
t Stat P-
value
Lower
95%
Up
per
95
%
Lower
95.0%
Upper
95.0%
Intercept 57250
2.60
53189.56 10.76 0.00 446729
.28
698
275
.91
44672
9.28
69827
5.91
Prices,
Consumer
Price Index,
All items,
Percentage
change,
Correspondin
g period
previous year,
Percent
24625
.09
30163.94 0.82 0.44 -
46701.
30
959
51.
47
-
46701.
30
95951.
47
Alpha
(Intercept)
57250
2.60
Slope 24625
.09
t-Test: Paired Two Sample for
Means
Particulars Price
s,
Cons
umer
Price
Other
financial
corporatio
ns and
money
6

Index
, All
items,
Perce
ntage
chang
e,
Corre
spond
ing
perio
d
previ
ous
year,
Perce
nt
market
funds;
gross
value
added
(IMA)
Mean 1.46 608345.78
Variance 1.11 777484211
4.44
Observations 9.00 9.00
Pearson
Correlation 0.29
Hypothesized
Mean
Difference
0.00
df 8.00
t Stat -20.70
P(T<=t) one-
tail 0.00
t Critical one-
tail 1.86
P(T<=t) two-
tail 0.00
t Critical two-
tail 2.31
R square stands for correlation coefficient which is determined through the regression analysis.
Higher value indicates the strong relationship between the given set of variables. In the given
case, R square is 90072.69.
For the simpler understanding, regression equation has been shown on the graph. It has been
observed that there has been a significant fluctuation in the variable ‘money market funds’. On
7

the other hand, variable namely, ‘consumer price index’ is showing the lesser fluctuation when
compared to the other variable. Alpha is technically known as intercept (Loeb&McFarland,
2017).
Alpha (Intercept) 572502.60
Slope 24625.09
Here, the two variables have been computed which are the most important output of regression
analysis. These two variables form the integral component of a regression analysis or
equation.Alpha is popularly known as intercept without which a suitable regression equation
cannot be formed or stated. In the case of CPI and money market funds, alpha has significant
value, i.e., 572502.60.
t-Test: Paired Two Sample for Means
Particulars Prices, Consumer Price
Index, All items, Percentage
change, Corresponding
period previous year, Percent
Other financial corporations
and money market funds;
gross value added (IMA)
Mean 1.46 608345.78
Variance 1.11 7774842114.44
Observations 9.00 9.00
Pearson Correlation 0.29
Hypothesized Mean Difference 0.00
df 8.00
t Stat -20.70
P(T<=t) one-tail 0.00
t Critical one-tail 1.86
P(T<=t) two-tail 0.00
t Critical two-tail 2.31
The above table depicts the t test that has been performed on the given variables. It can be clearly
observed that there is a positive relationship between the two given variables. Since, t test has
been performed on 9 variables in totality, the degree of freedom will be 8 (n-1), i.e., (9-1).
8

Conclusion
After carefully observing and analyzing all the variables, it can be observed that different
variables function different and thus it can be said that there are totally different output of
different economic variables. These economic variables can be either micro or macro.
Accordingly, it can be said that out of all the economic variables, some of the variables (majorly
micro variable) are controllable to some extent while remaining are not. In the given case, only
one variable of both category, i.e., dependent and independent has been taken into consideration
and therefore it can be said that amount pertaining to money market funds will be directly
affected by the Consumer Price index. A sudden change in CPI will clearly be shown in the
money market index.
9

References
 Harding, B., Tremblay, C., Cousineau, D., (2014). Standard Errors. School of Psychology,
Universitéd’ Ottawa, vol. 10, no. 2, 1-17.
 Loeb, S., McFarland, D., (2017). Descriptive analysis in education: A guide for researchers.
Institute of Education Sciences. 12(7). Pp. 1-40.
 Waltenburg, E., (2012). Exploratory Data Analysis: A Primer for Undergraduates. Department of
Political Science FacultyPublications. 6(4).Pp.1-69.
10