Instruction
Quantitative Analysis:
Assume that you are a consultant engaged in a project to implement a major high-speed overpass extension to the most congested highway, linking rural provinces to a major Asian city of 12 million people. A major feature of this project is to implement an electronic toll collection system for this high-speed segment. The objective of the entire project was not just to relieve congestion, lower the cost of operating vehicles, and improve the quality of transport services. It was also initiated to help address the loss of revenue resulting from an antiquated and corruption-ridden system of manual toll collection.
You helped implement the toll collection system and returned three years later to evaluate the effectiveness of the program. Data on toll collections and traffic volumes are available on a day-to-day basis. For this Discussion, review this weeks Learning Resources and examine the effectiveness of the project.
QUESTION: Post an explanation of how you would analyze data for this type of project. Include in your explanation the type of design and analysis you might use to address the problem.
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Analysis of Quantitative Data in Program Evaluation
Introduction
Assume that you have implemented your quantitative evaluation design, collected the relevant data, and you are now ready to answer questions about the effectiveness of your program. What techniques of analysis will you employ to answer the questions at the heart of your evaluation? You may or may not necessarily have a strong quantitative background or may be out of practice in statistical methods. Despite this, you realize you have to make the most out of the data you have collected.
This week, you examine the logic employed in program evaluation to select appropriate methods of data analysis.
Learning Objectives
Students will:
Analyze data to evaluate program effectiveness
Analyze multivariate techniques of data analysis
Analyze considerations relative to techniques of data analysis
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Required Resources
Readings
Langbein, L. (2012). Public program evaluation: A statistical guide (2nd ed.). Armonk, NY: ME Sharpe.
o Chapter 6, The Nonexperimental Design: Variations on the Multiple Regression Theme (pp. 143208)
McDavid, J. C., Huse, I., & Hawthorn, L. R. L. (2013). Program evaluation and performance measurement: An introduction to practice (2nd ed.). Thousand Oaks, CA: Sage.
o Chapter 7, Concepts and Issues in Economic Evaluation (pp. 271308)
Spiers, N., Manktelow, B., & Hewitt, M. J. (2009). Practical statistics using SPSS. Retrieved fromhttp://www.rds-yh.nihr.ac.uk/wp-content/uploads/2013/05/13_Practical_Statistics_Using_SPSS_Revision_2009.pdf
Walter, S. J. (2009). Using statistics in research. Retrieved from http://www.rds-yh.nihr.ac.uk/wp-content/uploads/2013/05/14_Using_Statistics_in_Research_Revision_2009.pdf
Institute for Digital Research and Education (IDRE). (n.d.). What statistical analysis should I use?Retrieved January 5, 2015, from http://www.ats.ucla.edu/stat/spss/whatstat/
Optional Resources
Blank, R. M. (2002). Evaluating welfare reform in the United States. Journal of Economic Literature, 40(4), 11051166.
Lance, P., Guilkey, D., Hattori, A., & Angeles, G. (2014). How do we know if a program made a difference? A guide to statistical methods for program impact evaluation. Retrieved fromhttp://www.cpc.unc.edu/measure/publications/ms-14-87-en
Evans, W. N., Farrelly, M. C., & Montgomery, E. (1999). Do workplace smoking bans reduce smoking?American Economic Review, 89(4), 728747.