Program Evaluation and Statistics
Program Evaluation and Statistics Textbook Order Form - PDF [71 KB]
This course is required in the Certificate in Fire Service Administration
In many ways, this course is designed like a sandwich. Just as a sandwich is a balance of complex carbohydrates like lettuce and bread on the one hand, and proteins like meat on the others, so Program Evaluation and Statistics is a balance as well. The “bread” is program evaluation, particularly found in Units 1 and 4. The “meat” is statistics sandwiched between Units 1 and 4 in Units 2 and 3.
Unit 1 (the first slice of bread) introduces program evaluation as a necessary part of any public program management. The Unit considers the pitfalls of over hasty evaluation and considers the logic of experimental design. The unit continues by indicating the practical limitations of experimental design and proceeds to introduce quasi experimental design. Finally the Unit ends with an introduction of the notion of statistical control, recognizing that the reader must learn some statistics before a discussion of program evaluation can continue.
Unit 2 introduces elementary notions of descriptive statistics. Beginning with definitions of key concepts, the Unit proceeds to consider sampling, frequency distributions, the presentation of these distributions. The unit ends with a presentation of measures of central tendency (particularly the mean) and measures of dispersion (particularly ‘variance’ and ‘standard deviation’).
Unit 3 considers bivariate relationships by introducing the Pearson Correlation Coefficient. The unit ends by considering a simple two variable regression model.
The statistical “meats” of Units 2 and 3 allow for a return to considerations of program evaluation in Unit 4 by an introduction to multiple regression. This introduction allows for an understanding of the concept of statistical control and helps to address some of the practical problems of program evaluation presented in Unit 1.
The “garnish for the sandwich” is Units on measurement. As a fire officer you will learn to have a productive conversation with evaluation researchers. One of the themes of such a conversation is measurement. You will know what is worth measuring better than the researcher. Once year communicate what you know the researcher will know better how to measure it.
Unit 1: Learning Objectives
Upon successful completion of this unit, you will be able to:
- describe Fayol's management cycle
- defend the importance of evaluation as a management tool
- explain why an organization might need to hire an evaluator
- appreciate some of the strengths and weaknesses of various forms of experimental design
Unit 2: Learning Objectives
Upon successful completion of this unit you will be able to:
- Answer the question what is statistics
- Differentiate between descriptive and inferential statistics
- Differentiate between a population and a sample
- Explain common sampling techniques
- Use frequency distribution to condense large masses of data
- Use graphs to present data
- Explain what is meant by central tendency
- Identify and compute means, medians and modes
- Compute mean deviations and standard deviations of a data set
Unit 4: Learning Objectives
Upon Successful completion of this unit you will be able to:
- Explain how some of the statistical techniques you have seen can be applied to program evaluation.
- Distinguish between the effects of independent variables on the dependent variable.
- Know when an experimental design will work or when statistical control may be necessary.
This course was written in 1994 by John Benoit, Associate Professor, Dalhousie University College of Continuing Education. John based the structure of much of this course, particularly Units 2 and 3, on lessons which were originally written for the Certificate in Property Assessment course entitled Statistical Tools for Assessment.
The original course was written in 1990 by Shingai Nyajeka, who is a former Research Associate for the Nova Scotia Department of Housing and Municipal Affairs.
We are deeply grateful to both John and Shingai for the quality of the course that their combined efforts has produced.
John Benoit, Ph.D.
John Benoit has been an applied sociologist, employing social science research to fire service administration. He obtained his PhD in sociology from the Johns Hopkins University in 1975, writing a dissertation on the effect of information flow on risk taking. He had worked at Dalhousie for 24 years, spending the last 20 as Director, Fire Management Education. During this time he wrote and co-wrote several of the courses, editing others. His principal areas of expertise include fire department-municipal government relations, the volunteer fire service, some aspects of personnel management, and theoretical perspectives on emergency management. In addition to course development, he has conducted research and published in the areas of volunteer fire administration, and disaster management. John recently retired and is now examining the effect of rural volunteer fire departments on the local community, and the impact of courageous experience and social capital on local economic development.