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SPSS Software Enables Babson College Students to Learn Statistics for the Real World
Students at Wellesley, Mass.-based Babson College are learning to apply statistics to real world applications using statistical software from SPSS Inc., a worldwide provider of predictive analytics technology and services. With the aid of SPSS(R) for Windows(R), SPSS Inc.'s flagship statistical and data management software, Babson students were recently able to apply the conceptual statistical analysis techniques they learned in the classroom to a real world experience with a Boston publication looking to identify the best places to live in Massachusetts.
"Teaching statistics in the classroom is one thing, but statisticians work outside of the classroom. My students must be adequately trained to handle the statistical challenges they will face in the real world," said I.
"Teaching statistics in the classroom is one thing, but statisticians work outside of the classroom. My students must be adequately trained to handle the statistical challenges they will face in the real world," said I.
Elaine Allen, associate professor of statistics and entrepreneurship at Babson College. "SPSS statistical software is the standard for classroom teaching because it enables students to hone their statistical analysis and develop practical problem-solving abilities that apply in the real world."
A recent example of the role SPSS plays in teaching Babson students real world applications of statistical analysis is the school's recent joint research project with Boston Magazine. This past April, Babson students were tasked with analyzing survey data for the publication's annual "Best Places to Live" issue.
For the project, the students compiled a ranking of 147 communities in Greater Boston, taking in to consideration the many factors that comprise living in a given community. Using the median home prices for each town as a baseline, the students considered the factors most important to homebuyers including costs (taxes and fees), quality of education, public safety, health, environment, lifestyle, and more. The students also incorporated survey data from real estate agents who were asked to prioritize the factors most important to homebuyers. The rankings were then developed by comparing each town's actual median housing price to a predicted housing price based on the town's characteristics.
Ultimately, Babson students named Marblehead, Mass. as the state's best place to live. Marblehead, which is near Boston's North Shore, scored highly in key areas while having a median home price of less than 45 percent of the most expensive community.
"Weighing the data and then testing our regression models was critical for the study, and we were impressed with the ability to easily move data back and forth between Microsoft(R) Excel(R) and SPSS without sacrificing productivity and data integrity," said Allen.
A recent example of the role SPSS plays in teaching Babson students real world applications of statistical analysis is the school's recent joint research project with Boston Magazine. This past April, Babson students were tasked with analyzing survey data for the publication's annual "Best Places to Live" issue.
For the project, the students compiled a ranking of 147 communities in Greater Boston, taking in to consideration the many factors that comprise living in a given community. Using the median home prices for each town as a baseline, the students considered the factors most important to homebuyers including costs (taxes and fees), quality of education, public safety, health, environment, lifestyle, and more. The students also incorporated survey data from real estate agents who were asked to prioritize the factors most important to homebuyers. The rankings were then developed by comparing each town's actual median housing price to a predicted housing price based on the town's characteristics.
Ultimately, Babson students named Marblehead, Mass. as the state's best place to live. Marblehead, which is near Boston's North Shore, scored highly in key areas while having a median home price of less than 45 percent of the most expensive community.
"Weighing the data and then testing our regression models was critical for the study, and we were impressed with the ability to easily move data back and forth between Microsoft(R) Excel(R) and SPSS without sacrificing productivity and data integrity," said Allen.
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