Type: Individual Project
Unit: Understanding Business Drivers and Improving
Business Forecasts
Due Date: Mon,
2/1/16
Grading Type: Numeric
Points Possible: 115
Points Earned: 0
Deliverable Length:
400–600 words
View objectives for this assignment
Explain the applications and limitations of statistical
hypothesis testing as applied to business situations.
Determine appropriate sampling methodologies for business
settings and situations
•Assignment Details
•Scenario
WidgeCorp became the market leader in snack foods after
acquiring a rival company, Company W. Their management style and business
decision-making differed. Employees at WidgeCorp collected relevant data and
through statistical analysis used this information to draw conclusions and make
appropriate recommendations. Company W tended to rely on the experience and
judgment of its managers. For the time being, both companies are being managed
separately, but within the next twelve months they will merge all management,
processes, and accounting. You work for Company W and are a little nervous
about this new way of working, but realize that you need to be able to present
issues and recommendations with statistical verification to the WidgeCorp
executives. You will also introduce and employ statistical analysis to the
senior management of Company W’s various departments such as Marketing, Sales,
and Production. Part of your job will be to educate Company W as well.
Assignment
Description
Weekly tasks or assignments (Individual or Group Projects)
will be due by Monday, and late submissions will be assigned a late penalty in
accordance with the late penalty policy found in the syllabus. NOTE: All
submission posting times are based on midnight Central Time.
You are in a brainstorming session at WidgeCorp, where no
idea is too outrageous. You are discussing penetration in the school lunch
market. Ideas around school lunch subsidies, Internet subsidies, and Internet
target marketing are being discussed. As the end of the meeting, the group asks
you to prove or disprove some assumptions by looking at correlations.
First, acquaint yourself with the Internet subsidy issue by
reading the article Closing the Digital Divide: Internet Subsidies in Public
Schools by Austan D. Goolsbee and Jonathan Guryan. See the article below…
Vol. 5 No. 1| Summer 2003
IN THIS ISSUE
Banner Ads Click with Consumers
Closing the Digital
Divide
Buy, Sell, or Hold
The $4 Trillion Question
Closing the Digital
Divide
Internet Subsidies in
Public Schools
Research by Austan D. Goolsbee and Jonathan Guryan
As Internet use has
dramatically increased over the past five years, policymakers have grown
concerned about the so-called “digital divide,” in which access and
understanding of technology would be split across income and racial lines. New
research analyzes the impact of an ambitious federal technology program aimed
to bridge the digital divide in public schools.
Policymakers and
analysts have argued that public schools are a natural place to teach
underserved populations about computers and increase access to new technology.
As part of the Telecommunications Act of 1996, the government began actively
subsidizing Internet and telecommunications access in U.S. classrooms and
libraries through a tax on long-distance telephone services.
Starting in 1998 and continuing today, the E-Rate program
provides $2.25 billion annually in subsidies to schools and libraries so they
can invest in Internet and communications technology. This is especially
significant when compared to the combined computer budget in all public
schools, which totaled only $3.3 billion in 1999.
In their new study, “The Impact of Internet Subsidies
in Public Schools,” University of Chicago Graduate School of Business
professors Austan D. Goolsbee and Jonathan Guryan provide the first step
towards evaluating the effect of the E-Rate subsidy on Internet investment in
California public schools.
“The effect of differing access to technology can
magnify as people get older, so the subsidy may function as preventive
medicine,” says Guryan.
Goolsbee and Guryan approached their study with two goals in
mind: 1) to understand the extent to which the $2.25 billion subsidy fulfilled
its primary goal of increasing Internet usage in schools, particularly those
serving disadvantaged students, versus merely subsidizing spending that was
already taking place; and 2) addressing the considerable interest in and debate
about whether spending on computers and information technology has any impact
on student performance.
Employing new data on school technology usage in every
California public school from 1996 to 2000, as well as application data from
the E-Rate program, Goolsbee and Guryan find that the subsidy did succeed in
significantly increasing schools’ investment in Internet technology. By 2000,
there were approximately 66 percent more classrooms in California with Internet
connections than there would have been without the subsidy-the equivalent of
accelerating Internet investment by about four years.
Despite the noticeable increase in classroom Internet
connections, the authors find very little evidence that the program has any
impact on student achievement, as measured by test scores in a variety of
subjects.
Analyzing the E-Rate
The E-Rate program was designed to give all eligible schools
and libraries affordable access to modern telecommunications and information
services. The subsidy can be used for spending on all commercially available
telecommunications services, Internet access, and internal communications, but
not for buying computers for the school. The subsidy rate ranges from 20 to 90
percent depending on the school’s share of students that qualify for the
national school lunch program.
The federal government subsidizes or gives free school
lunches to students whose family income is below a certain level, usually close
to the poverty level. The number of school lunch eligible students determines
funding for many federal and state education-related programs. The higher that
number is, the higher the subsidy rate.
By 1997, the year before the first E-Rate funding was
awarded, 55 percent of California’s public schools had at least one classroom
with Internet access, an increase of 9 percentage points from 1996. Even
without subsidies, many school districts chose to make Internet investments. It
is therefore difficult to distinguish between the effects of the E-Rate program
alone versus the already strong upward trend in the fraction of schools with
Internet access.
To address this concern, Goolsbee and Guryan used new data
on the information technology owned in each year by every school in California.
They merged this with administrative data on every E-Rate funding application
these same schools filed, including the amount of funding, the subsidy rate,
and the purpose of the funding. They also included demographic data for each
school and district from the National Center for Education Statistics Common
Core of Data and the 1990 U.S. Census.
California was chosen primarily because the state was
already measuring technology usage at schools before the E-Rate program
started.
“The fact that we were able to get detailed data on
individual schools and what they had purchased before the E-Rate began is what
allowed us to identify the impact of the program separately from just
underlying trends in the economy,” says Goolsbee.
From 1996 to 1997, the richest California schools had almost
50 percent more Internet classrooms per teacher than the poorest group. Over
the next year, this gap increased. Once the E-Rate program began in 1998,
however, the poorer groups began receiving large subsidies relative to the
richest group, making Internet connections much more affordable. Their relative
number of Internet connections accelerated and by 2000, some of the poorest
school districts actually had more Internet connections than the richest school
districts.
Goolsbee and Guryan find that most of the E-Rate funds went
to schools with subsidy rates of 80 to 90 percent-schools with more than 50
percent of their students eligible for free or reduced price lunches from the
federal government.
This reversal in the Internet access rates of rich and poor
schools indicates a closing of the digital divide that occurred in the years
following the introduction of the E-Rate program.
Rural schools are substantially less responsive to the
subsidy than urban schools. The subsidies had the greatest impact on schools
with heavily black and Hispanic student populations. Schools with a majority of
white and Asian students did not show a significant increase in Internet
connections. Elementary schools also respond to the subsidy to a greater degree
than high schools.
“As a technology subsidy, the E-Rate program is a
tremendous success,” says Goolsbee. “Today, the majority of
classrooms in schools are connected to the Internet.”
Gauging Student Performance
Having established that the E-Rate program achieved its
primary goal of getting classrooms connected to the Internet, particularly at
disadvantaged schools, Goolsbee and Guryan extended their evaluation to the
next logical level: Does this investment in technology have any impact on
student performance?
Many of the most prominent supporters of the E-Rate program
argued that the program should aspire to more than just wiring schools, and
should help students develop basic skills.
Goolsbee and Guryan measured student achievement using the
Stanford Achievement Test, which has been given every year to all elementary,
middle, and high school students in California public schools beginning with
the 1997-98 school year. They used three measures of school-level achievement:
the average test score in the school, the fraction of students scoring above
the 75th percentile score for the state, and the fraction of students scoring
above the 25th percentile score for the state.
The authors looked at test scores for math, reading, and
science. Their results showed no evidence that investments in Internet
technology had any measurable effect on student achievement. However, they note
that it may be too early to evaluate long-term investments in information
technology, or that gains may have taken place in areas other than test scores.
The lack of impact on student performance is consistent with
Department of Education evidence that only one-third of teachers reported they
were prepared or well-prepared to use computers and the Internet in the
classroom. If teachers are uncomfortable working with the technology or
computers in general, it is easy to see why greater Internet access may not
directly result in better prepared students.
“It certainly would have been great if you spent a
modest amount of money on this program and saw a big educational bang for the
buck,” says Goolsbee. “But for researchers it’s not surprising that
the subsidy did not have this effect, because there is no magic bullet for improving
student performance.”
Making the Internet Work in Classrooms
Goolsbee and Guryan suggest the next step for studying
effects of the E-Rate program would be to figure out why the high rates of
Internet adoption have had a minimal impact on student performance.
“One possibility would be to run pilot programs,
collect data, and see how schools are using the technology,” says Guryan.
“Are there schools that introduce the technology very effectively? What
kind of schools are they? What are the skills that teachers need to be able to
use the Internet?”
The authors highlight the importance of finding out what the
technology actually achieves in the classroom, and whether teachers are even
incorporating the Internet into the curriculum. Getting classrooms connected is
only the first hurdle toward eliminating the digital divide.
Austan D. Goolsbee is professor of economics at the
University of Chicago Graduate School of Business. Jonathan Guryan is assistant
professor of economics at the University of Chicago Graduate School of
Business.
Next, download the file Sample Data. Based on the findings
as reported in this article, prepare a chart similar to the one in the
downloaded file to indicate if the correlation between Variables A and B were
found to be positive, negative, or minimal.
Sample data download: see below
VARIABLE A
VARIABLE B
CORRELATION: POSITIVE, NEGATIVE, MINIMAL?
Number of school lunch eligible students in the school
Amount of funding received by the school for federal state
education-related programs
Impact of subsidy received
Age of students at school
Number of classrooms connected to the internet
Student performance, as measured by standardized test scores.
Teacher’s comfort level with the internet.
Ability of teachers to use internet effectively with their
students
running_he79.docxType: Individual Project
Unit: Understanding Business Drivers and Improving Business Forecasts
Due Date: Mon, 2/1/16
Grading Type: Numeric
Points Possible: 115
Points Earned: 0
Deliverable Length: 400–600 words
View objectives for this assignment
Explain the applications and limitations of statistical hypothesis testing as applied to business situations.
Determine appropriate sampling methodologies for business settings and situations
•Assignment Details
•Scenario
WidgeCorp became the market leader in snack foods after acquiring a rival company, Company W. Their
management style and business decision-making differed. Employees at WidgeCorp collected relevant
data and through statistical analysis used this information to draw conclusions and make appropriate
recommendations. Company W tended to rely on the experience and judgment of its managers. For the
time being, both companies are being managed separately, but within the next twelve months they will
merge all management, processes, and accounting. You work for Company W and are a little nervous
about this new way of working, but realize that you need to be able to present issues and
recommendations with statistical verification to the WidgeCorp executives. You will also introduce and
employ statistical analysis to the senior management of Company W’s various departments such as
Marketing, Sales, and Production. Part of your job will be to educate Company W as well.
Assignment Description
Weekly tasks or assignments (Individual or Group Projects) will be due by Monday, and late submissions
will be assigned a late penalty in accordance with the late penalty policy found in the syllabus. NOTE: All
submission posting times are based on midnight Central Time.
You are in a brainstorming session at WidgeCorp, where no idea is too outrageous. You are discussing
penetration in the school lunch market. Ideas around school lunch subsidies, Internet subsidies, and
Internet target marketing are being discussed. As the end of the meeting, the group asks you to prove or
disprove some assumptions by looking at correlations.
First, acquaint yourself with the Internet subsidy issue by reading the article Closing the Digital Divide:
Internet Subsidies in Public Schools by Austan D. Goolsbee and Jonathan Guryan. See the article below…
Vol. 5 No. 1| Summer 2003
IN THIS ISSUE
Banner Ads Click with Consumers
Closing the Digital Divide
Buy, Sell, or Hold
The $4 Trillion Question
Closing the Digital Divide
Internet Subsidies in Public Schools
Research by Austan D. Goolsbee and Jonathan Guryan
As Internet use has dramatically increased over the past five years, policymakers have grown concerned
about the so-called “digital divide,” in which access and understanding of technology would be split
across income and racial lines. New research analyzes the impact of an ambitious federal technology
program aimed to bridge the digital divide in public schools.
Policymakers and analysts have argued that public schools are a natural place to teach underserved
populations about computers and increase access to new technology. As part of the
Telecommunications Act of 1996, the government began actively subsidizing Internet and
telecommunications access in U.S. classrooms and libraries through a tax on long-distance telephone
services.
Starting in 1998 and continuing today, the E-Rate program provides $2.25 billion annually in subsidies to
schools and libraries so they can invest in Internet and communications technology. This is especially
significant when compared to the combined computer budget in all public schools, which totaled only
$3.3 billion in 1999.
In their new study, “The Impact of Internet Subsidies in Public Schools,” University of Chicago Graduate
School of Business professors Austan D. Goolsbee and Jonathan Guryan provide the first step towards
evaluating the effect of the E-Rate subsidy on Internet investment in California public schools.
“The effect of differing access to technology can magnify as people get older, so the subsidy may
function as preventive medicine,” says Guryan.
Goolsbee and Guryan approached their study with two goals in mind: 1) to understand the extent to
which the $2.25 billion subsidy fulfilled its primary goal of increasing Internet usage in schools,
particularly those serving disadvantaged students, versus merely subsidizing spending that was already
taking place; and 2) addressing the considerable interest in and debate about whether spending on
computers and information technology has any impact on student performance.
Employing new data on school technology usage in every California public school from 1996 to 2000, as
well as application data from the E-Rate program, Goolsbee and Guryan find that the subsidy did
succeed in significantly increasing schools’ investment in Internet technology. By 2000, there were
approximately 66 percent more classrooms in California with Internet connections than there would
have been without the subsidy-the equivalent of accelerating Internet investment by about four years.
Despite the noticeable increase in classroom Internet connections, the authors find very little evidence
that the program has any impact on student achievement, as measured by test scores in a variety of
subjects.
Analyzing the E-Rate
The E-Rate program was designed to give all eligible schools and libraries affordable access to modern
telecommunications and information services. The subsidy can be used for spending on all commercially
available telecommunications services, Internet access, and internal communications, but not for buying
computers for the school. The subsidy rate ranges from 20 to 90 percent depending on the school’s
share of students that qualify for the national school lunch program.
The federal government subsidizes or gives free school lunches to students whose family income is
below a certain level, usually close to the poverty level. The number of school lunch eligible students
determines funding for many federal and state education-related programs. The higher that number is,
the higher the subsidy rate.
By 1997, the year before the first E-Rate funding was awarded, 55 percent of California’s public schools
had at least one classroom with Internet access, an increase of 9 percentage points from 1996. Even
without subsidies, many school districts chose to make Internet investments. It is therefore difficult to
distinguish between the effects of the E-Rate program alone versus the already strong upward trend in
the fraction of schools with Internet access.
To address this concern, Goolsbee and Guryan used new data on the information technology owned in
each year by every school in California. They merged this with administrative data on every E-Rate
funding application these same schools filed, including the amount of funding, the subsidy rate, and the
purpose of the funding. They also included demographic data for each school and district from the
National Center for Education Statistics Common Core of Data and the 1990 U.S. Census.
California was chosen primarily because the state was already measuring technology usage at schools
before the E-Rate program started.
“The fact that we were able to get detailed data on individual schools and what they had purchased
before the E-Rate began is what allowed us to identify the impact of the program separately from just
underlying trends in the economy,” says Goolsbee.
From 1996 to 1997, the richest California schools had almost 50 percent more Internet classrooms per
teacher than the poorest group. Over the next year, this gap increased. Once the E-Rate program began
in 1998, however, the poorer groups began receiving large subsidies relative to the richest group,
making Internet connections much more affordable. Their relative number of Internet connections
accelerated and by 2000, some of the poorest school districts actually had more Internet connections
than the richest school districts.
Goolsbee and Guryan find that most of the E-Rate funds went to schools with subsidy rates of 80 to 90
percent-schools with more than 50 percent of their students eligible for free or reduced price lunches
from the federal government.
This reversal in the Internet access rates of rich and poor schools indicates a closing of the digital divide
that occurred in the years following the introduction of the E-Rate program.
Rural schools are substantially less responsive to the subsidy than urban schools. The subsidies had the
greatest impact on schools with heavily black and Hispanic student populations. Schools with a majority
of white and Asian students did not show a significant increase in Internet connections. Elementary
schools also respond to the subsidy to a greater degree than high schools.
“As a technology subsidy, the E-Rate program is a tremendous success,” says Goolsbee. “Today, the
majority of classrooms in schools are connected to the Internet.”
Gauging Student Performance
Having established that the E-Rate program achieved its primary goal of getting classrooms connected
to the Internet, particularly at disadvantaged schools, Goolsbee and Guryan extended their evaluation
to the next logical level: Does this investment in technology have any impact on student performance?
Many of the most prominent supporters of the E-Rate program argued that the program should aspire
to more than just wiring schools, and should help students develop basic skills.
Goolsbee and Guryan measured student achievement using the Stanford Achievement Test, which has
been given every year to all elementary, middle, and high school students in California public schools
beginning with the 1997-98 school year. They used three measures of school-level achievement: the
average test score in the school, the fraction of students scoring above the 75th percentile score for the
state, and the fraction of students scoring above the 25th percentile score for the state.
The authors looked at test scores for math, reading, and science. Their results showed no evidence that
investments in Internet technology had any measurable effect on student achievement. However, they
note that it may be too early to evaluate long-term investments in information technology, or that gains
may have taken place in areas other than test scores.
The lack of impact on student performance is consistent with Department of Education evidence that
only one-third of teachers reported they were prepared or well-prepared to use computers and the
Internet in the classroom. If teachers are uncomfortable working with the technology or computers in
general, it is easy to see why greater Internet access may not directly result in better prepared students.
“It certainly would have been great if you spent a modest amount of money on this program and saw a
big educational bang for the buck,” says Goolsbee. “But for researchers it’s not surprising that the
subsidy did not have this effect, because there is no magic bullet for improving student performance.”
Making the Internet Work in Classrooms
Goolsbee and Guryan suggest the next step for studying effects of the E-Rate program would be to
figure out why the high rates of Internet adoption have had a minimal impact on student performance.
“One possibility would be to run pilot programs, collect data, and see how schools are using the
technology,” says Guryan. “Are there schools that introduce the technology very effectively? What kind
of schools are they? What are the skills that teachers need to be able to use the Internet?”
The authors highlight the importance of finding out what the technology actually achieves in the
classroom, and whether teachers are even incorporating the Internet into the curriculum. Getting
classrooms connected is only the first hurdle toward eliminating the digital divide.
Austan D. Goolsbee is professor of economics at the University of Chicago Graduate School of Business.
Jonathan Guryan is assistant professor of economics at the University of Chicago Graduate School of
Business.
Next, download the file Sample Data. Based on the findings as reported in this article, prepare a chart
similar to the one in the downloaded file to indicate if the correlation between Variables A and B were
found to be positive, negative, or minimal.
Sample data download: see below
VARIABLE A
VARIABLE B
Number of school lunch
eligible students in the
school
Amount of
funding received by the
school for federal state
education-related
programs
Impact of subsidy
received
Age of students at school
Number of classrooms
connected to the internet
Student performance, as
measured by
standardized test scores.
Teacher’s comfort level
with the internet.
Ability of teachers to use
internet effectively with
CORRELATION: POSITIVE,
NEGATIVE, MINIMAL?
their students
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