Diablo Valley College
Business 240
Chapters 6 - 8
Spring 2010
Exam #2
Maximum points: 150. Show your work (all steps and reasoning) in order to earn full credit in your
responses.
Your name: __________________________________
1. [50 points] Business regulation is measured by using “REG”, an Index of Regulation ranging from 1 to
50 (1 least regulatory State, and 50 most burdensome regulatory State). REG partially explains the level
of economic activity in the State of California, or Gross State Product, “GSP”, measured in $Millions (this,
according to “Cost of State Regulations on California Small Businesses Study”, by Sanjay Varshney and
Dennis Tootelian). The linear model below shows a partial model of the relation between Gross State
Product (GSP) and the “Extent of Regulation” Faced by Businesses in California (REG):
GSP = 2000566 – 12450.16*REG
The model they estimated had an R2 = 40.0093%.
a)
(10 points) What are the numeric values and the units of measurement of the intercept and the
slope in the above regression line?
Coefficient
Magnitude
Units
Intercept
Slope
b)
(20 points) If California ranks 40th (REG = 40) among states in regulation burden terms, then
what is the impact (direction and magnitude) of regulations on our State’s economy, in $Billions or
in $Millions?
c)
(10 points) Derive the correlation coefficient between GSP and REG from the given coefficient of
determination, R2.
d)
(10 points) Determine the direction and the strength of the linear association between GSP and
REG from the correlation coefficient in the previous part.
2. [100 points] Environmental issues have risen in economic and business importance over the last two
decades. In particular, many persons believe that economic growth is directly related to increases in
emissions of pollutants. This problem will examine the relation between economic growth, as measured
by production and consumption variables, versus emissions of a host of gases deemed pollutants by
commercial and environmental law in the United States.
The
data
for
this
problem
is
available
on
the
voyager
http://voyager2.dvc.edu/~alacayo/bus240_exam_exam2_fa10.htm. Please load this
STATCRUNCH and perform the tasks requested below.
site
data
at
into
The filename is EPEQUS.csv and contains data from the National Air Pollutant Emission Trends, 19471998. The data has been indexed to a base year of 1947 (1947 = 100). The data source is URL:
http://www.economagic.com/em-cgi/data.exe/beanat/t102101:q2a+a. The data set also contains two
other variables, in indexed form, that measure U.S. output (real Gross Domestic Product—indexed) and
U.S. Consumption (real Consumption—indexed)
a) (10 points) Use statcrunch to produce a time series plot of U.S. GDP and U.S. Consumption.
Paste the plot below and describe the three main features of the two time series in this graph
(trend, cycle and volatility).
b) (10 points) Use statcrunch to calculate the correlation between these two series. Describe the
direction and strength of the relation between U.S. GDP and U.S. Consumption.
c) (10 points) Use statcrunch to produce a time series plot of the following pollutants: CO, SO2,
NOX, PM10, and VOC. Paste the plot below and describe the three main features of the two time
series in this graph (trend, cycle and volatility).
d) (10 points) Use statcrunch to calculate the correlation coefficient table for all of the correlations
over time between the above pollutants. Describe the direction and the strength of the
relationship between these five industrial pollutants.
e) (10 points) Consider the following simple linear model: CO = b + m*USrealGDP. This model
states that the emission of CO (Y) is explained by the level of economic activity USrealGDP (X) in
a linear manner, such that b = constant/y-intercept and m = slope of the linear relation. Use
statcrunch to compute the simple linear regression above and paste the summary regression
results below.
f)
(10 points) In the regression of part (e), use statcrunch to graph the fitted regression line and
paste a copy of the scatter plot with the fitted regression line below.
g) (10 points) Does it make sense to interpret the intercept estimate, b, of the simple regression line
of part (e)? Explain why the intercept’s meaning may be irrelevant.
h) (20 points) Interpret the meaning of the slope estimate, m, from the output in part (f).
i)
(10 points) Use the scatter plot to confirm that it is fair to conclude that, over the past thirty years,
CO emissions are declining as the economy has grown. But, why does the regression NOT back
up this conclusion?