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PPA 415 – Statistical Methods in Public Administration

PPA 415 – Statistical Methods in Public Administration. Lecture 1c – Research Design Summary. Research Questions. Research questions can be descriptive. What is happening to a variable currently or what will happen in the future? Research questions can be causal.

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PPA 415 – Statistical Methods in Public Administration

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  1. PPA 415 – Statistical Methods in Public Administration Lecture 1c – Research Design Summary

  2. Research Questions • Research questions can be descriptive. • What is happening to a variable currently or what will happen in the future? • Research questions can be causal. • What factors are causing a variable to change? • What factors influence the key variables in the research question?

  3. Variables • Concepts, variables, indicators. • Causal direction. • Independent variables (causes). • Dependent variables (effects).

  4. Hypotheses • Hypotheses can be descriptive. • Are arrests for DUI increasing over time? • Hypotheses can also be causal. • Do increases in DUI arrests reduce deaths in motor vehicle accidents? • Does nearness to a presidential election increase the likelihood of granting a major disaster declaration?

  5. Sampling • Population (states, counties, IAEM members). • Random samples (simple, systematic, cluster, random digit dialing). • Snowball sampling • Purposive or haphazard sampling.

  6. Data Collection Procedures • Surveys. • Agency records and primary documents. • Direct observation. • Existing data sets (Census, BLS, ICPSR, etc.). www.fedstats.gov. • Participant observation. • Focus groups. • Literature review.

  7. Data Analysis Procedures – Quantitative (What, Where, When) • Descriptive statistics (mean, median, mode, standard deviation). • Inferential statistics. • T-tests, analyses of variance, chi-square, cross tabulation. • Measures of association. • Bivariate. • Regression-based analysis. • Multivariate analysis. • Multiple regression, analysis of covariance, logistic regression. • Data reduction (factor analysis, scaling).

  8. Data Analysis Procedures – Qualitative (Why, How). • Focus group summaries. • Interview summaries. • Historical analysis. • Content analysis. • Case studies. • Ethnography. • Participant observation.

  9. Interpretation, Conclusions • Looking for answers to research questions. • Quantitative research often asks what, where, and when. Focuses on common elements across subjects. Makes inferences to whole population. • Qualitative research asks why and how. Focuses on what is unique across subjects. Makes in-depth analysis of complexities of choice.

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