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Confidence Intervals and Hypothesis Testing

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Confidence Intervals and Hypothesis Testing

In this topic, students learn the theory and methods of confidence intervals and hypothesis testing. Confidence intervals assess how well a sample statistic estimates the corresponding population value (U.S. National Institute of Standards and Technology). Hypothesis testing is a related component that assesses whether there is a statistically significant difference between the treatment group and control group in an experiment.

Topic Learning Outcome: Students will have a working knowledge of how researchers test hypotheses, and will be able to perform hypothesis tests of their own using statistical software.

Core Concepts associated with this Topic: Causal Relationship; Histogram; Standard Error; Validity (internal and external).

Recommended Readings

Toronto: PPG1004H Quantitative Methods for Policy Analysis, Fall 2012

Stock, James H. and Mark W. Watson. 2011. “Introduction to Econometrics.” 3rd edition. Pearson/Addison-Wesley. Chapter 3 (p. 70-90 and p. 91-96) and Chapter 4 (p. 107-112).

Harvard: API-201 Quantitative Analysis and Emprical Methods, Fall 2014

Moore, David S., George P. McCabe, and Bruce Craig. 2014. “Introduction to the Practice of Statistics.” 8th Edition. Sections:

Sampling Distributions for Proportions: 3.3 (pp. 202-206) and 5.2 (pp. 312-326)

Confidence Intervals for Proportions: 6.1 (pp. 344-347) and 8.1 (pp. 474-478)

Statistical Inference for Proportions: 6.2 (pp. 360-369)

Statistical Inference for Means: 6.1 (pp. 348-end), 6.2 (pp. 370-end), 7.1

Statistical Inference for Differences: 7.2, 8.2

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 7 (pp. 154-172), 8, 9.

Blustein, J. “SPSS: The Wagner Way.” Chapter 4.

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

Leo H. Kahane. 2008. “Regression Basics,” Thousand Oaks: Sage. Chapter 3.

Tufte, Edward. 1974. “Data Analysis for Politics and Policy.” Englewood Cliffs, N.J.: Prentice-Hall. Chapter 3, “Example 5: Comparing the Slope and the Correlation Coefficient”, pp. 101-107.

Achen, Christopher H. “Interpreting and Using Regression.” Chapter 4, “Comparing Substantive and Statistical Significance”, pp. 46-51. http://library.usask.ca/scripts/remote?URL=http://dx.doi.org/10.4135/9781412984560.n4

Newhouse, Joseph P. “Medical-Care Expenditure: A Cross-National Survey,” Journal of Human Resources, 12:1 (Winter 1977), pp.115-125. http://library.usask.ca/scripts/remote?URL=http://www.jstor.org/stable/pdfplus/145602.pdf?acceptTC=true 

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

Healey, J.H. 2011. “Statistics. A tool for social research.” 9th edition. Thompson, Wadsworth. Chapters 8 and 9.

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

De Veaux, Richard D., Paul F. Velleman, and David E. Bock. 2011. “Stats: Data and Models.” 3rd edition. Boston: Pearson Education. Syllabus sections and corresponding chapters:

Standard Errors & Confidence Intervals for Means and Proportions: Chapters 19 & 23

Hypothesis Testing: One Proportion or Mean: 20 & 21

Hypothesis Testing: Power, Comparing Two Proportions or Means, Paired T-tests: 22, 24, 25

Hypothesis Testing: Comparing more than two means (ANOVA): 28

Hypothesis Testing: Two Categorical Variables: 26

Rutgers: 34:833:530 Analytical Methods I: Research Design, Fall 2013

Wang, Xiaohu. 2010. “Performance Analysis for Public and Nonprofit Organizations.” Jones and Bartlett Publishers. Chapter 7.

 

Sample Assessment Questions:

1.) What is a P-value? Why is this statistic important for confidence testing?

2.) What does the term "statistical significance at the 5 percent level" mean?

 

Page created by Sean Goertzen on 4 November 2014; updated by Ben Eisen on 19 May 2015.

  


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© University of Toronto 2008
School of Public Policy and Governance