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Looking at Data

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Looking at Data

This topic teaches students about different types of data sets and different ways of representing data. Students learn how to familiarize themselves with new, complicated data sets. This topic will usually include some instruction in the use of various software programs to interpret, analyze and present data. Students learn how to use graphics and figures to represent data and convey complicated, important information in an interesting, memorable way.

Topic Learning Outcome: Upon mastering this topic, students will have experience with the process of familiarizing themselves with and learning to understand new and increasingly complicated data sets. Students will be familiar with at least one statistical software program, and will understand how tables, charts and graphs can be used to present complicated information in a digestible way. 

Core Concepts Associated With This Topic: Data; Dataset; Frequency Distribution; Indicator; Quantitative Research; Quartile; Unit of Analysis

Recommended Reading

Carleton: PADM 5114 Research Methods and Design II, Winter 2014

Moore, D., McCabe G., & Craig, B. 2009. “Introduction to the Practice of Statistics, Sixth Edition.” New York: W. H. Freeman and Company. Chapters 1 – 2.

Wagner: GP.1011 Statistical Methods for Public, Nonprofit, and Health Management, Fall 2014

Healey, Joseph F. 2013. “The Essentials of Statistics: A Tool for Social Research.” 2nd edition. Wadsworth/Cengage Learning. Chapters 1 - 3.

Blustein, J. “SPSS: The Wagner Way.” Chapter 1.

Saskatchewan-Regina: JSGS 803 Quantitative Methods and Research Design, Fall 2013

Syllabus Section: Overview of Statistical Analysis (statistical inference, probability distributions, sampling distributions, scales of measurement, variables and constants, hypothesis testing, Type 1 and Type 2 errors, significance levels)

Garnet Picot, “Does Statistical Analysis Matter?” Horizons, 6:1 (Policy Research Initiative: 2003), pp. 6-10. http://dsp-psd.pwgsc.gc.ca/Collection/CP12-1-6-1E.pdf

Joel Best, More Damned Lies and Statistics: How Numbers Confuse Public Issues, (Berkeley: University of California Press, 2004) Chapter 6 “Contentious Numbers”.

Syllabus Section: Diagnostics and Data Transformations (multicollinearity, outliers, non-normality, homoscedasticity, and nonlinearity)

Leo H. Kahane, “Regression Basics,” (Thousand Oaks: Sage, 2008). Chapter 5, pp. 79-83, Chapter 7.

Robert W. Jackman, "The Politics of Economic Growth in the Industrial Democracies, 1974-80: Leftist Strength or North Sea Oil?," The Journal of Politics, 49:1 (Feb. 1987), pp. 242-256. http://library.usask.ca/scripts/remote?URL=http://www.jstor.org/stable/2131143

Joseph G. Nagy and W. Hartley Furtan, “Economic Costs and Returns from Crop Development Research: The Case of Rapeseed Breeding in Canada,” Canadian Journal of Agriculture Economics 26:1 (Feb. 1978), pp. 1-14. http://library.usask.ca/scripts/remote?URL=http://dx.doi.org/10.1111/j.1744-7976.1978.tb02894.x

American: PUAD 605 Quantitative Methods for Public Managers, Fall 2012

Syllabus Section: Introduction to Statistics; The Role of Statistics in Public Administration Research; Data, Variables; Introduction to SPSS in the classroom

Healey, J.H. 2011. “Statistics. A tool for social research.” 9th edition. Thompson, Wadsworth. Prologue: Basic Mathematics Review on page XXIII.

UCLA: PUB PLC 203 Statistical Methods for Public Policy I, Fall 2013

Syllabus Section: Introduction to the Data; Research Designs; Sampling Basics; Displaying Data

De Veaux, Richard D., Paul F. Velleman, and David E. Bock. 2011. “Stats: Data and Models.” 3rd edition. Boston: Pearson Education. Chapters 1-3; Chapters 12-13.

Rutgers: 34:833:530 Analytical Methods, Fall 2013

Syllabus Section: Measurement and Data Collection

Wang, Xiaohu. 2010. “Performance Analysis for Public and Nonprofit Organizations.” Jones and Bartlett Publishers. Chapter 2.

Berman, Evan M., and Xiaohu Wang. 2012. “Essential Statistics for Public Managers and Policy Analysts.” 3rd edition. Thousand Oaks. Chapters 3 - 4.

Possible Assessment Questions:

1.)   Why are graphs and figures sometimes useful in helping audiences understand data?

2.)   How have software programs like STATA and SPSS changed data analysis?

3.)   What is a frequency distribution?

Page created by Ben Eisen and Sean Goertzen on 4 November 2014

 


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