Statistically Significant Differences? Students from Developing Areas and the Developing Area of Quantitative Reasoning

  • J. Mark Davidson Schuster
Part of the Urban Innovation Abroad book series (UIA)


Most of the chapters in this volume address the question: What is the appropriate planning education for students from developing areas? In this chapter I turn this question on its head, asking instead: What is the best way to teach the material with which I have been charged and what does the presence of developing areas students in my course teach me about my teaching?


International Student Number Sense Statistical Hypothesis Testing Planning Practice Planning Curriculum 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Alonso, W., and Starr, P., 1987, “The Politics of Numbers,” Russell Sage, New York.Google Scholar
  2. Blalock, H. M., Jr., 1972, “Social Statistics,” McGraw-Hill, New York.Google Scholar
  3. Bureau of Labor Statistics, 1976, “Handbook of Methods for Surveys and Studies,” Bulletin 1910, US Department of Labor, Washington, D.C.Google Scholar
  4. de Neufville, J.I., 1984, Functions of Statistics in Planning, paper presented at the Annual Conference of the Association of Collegiate Schools of Planning, October 19–21, New York.Google Scholar
  5. Dunn, W.N., 1981, “Public Policy Analysis: An Introduction,” Prentice-Hall, Englewood Cliffs, New Jersey.Google Scholar
  6. Freedman, D., Pisani, R., and Purves, R., 1978, “Statistics,” W.W. Norton, New York.Google Scholar
  7. Gerard, K., 1984, “American Survivors: Cities and Other Scenes,” Chapter 11: Why can’t economists say, ‘I don’t know’?, Harcourt Brace Jovanovich, San Diego.Google Scholar
  8. Hambrick, R.S., 1974, A guide for the analysis of policy arguments, Policy Sciences, 5:469.CrossRefGoogle Scholar
  9. Hardin, G., 1985, “Filters Against Folly: How to Survive Despite Economists, Ecologists, and the Merely Eloquent,” Viking, New York.Google Scholar
  10. Harte, J., 1985, “Consider a Spherical Cow: A Course in Environmental Problem Solving,” William Kaufmann, Los Altos, California.Google Scholar
  11. Hastings, W.N., 1979, “How to Think About Social Problems: A Primer for Citizens,” Oxford University Press, New York.Google Scholar
  12. Helias, P-J., 1978, “The Horse of Pride: Life in a Breton Village,” Yale University Press, New Haven, pp. 154–157.Google Scholar
  13. Hodge, G., 1963, The use and mis-use of measurement scales in city planning, Journal of the American Institute of Planners, 2: 112.CrossRefGoogle Scholar
  14. Horwitz, L., and Ferleger, L., 1980, “Statistics for Social Change,” South End Press, Boston.Google Scholar
  15. Hyman, R., and Price, B., 1979, Labour Statistics, in: “Demystifying Social Statistics,” J. Irvine, I. Miles, and J. Evans, eds., Pluto Press, London.Google Scholar
  16. Irvine, J., Miles, I., and Evans, J., eds., 1979, “Demystifying Social Statistics,” Pluto Press, London.Google Scholar
  17. Johnston, D., 1983, Census concepts as knowledge filters for public policy advisors, Knowledge, Creation, Diffusion, Utilization, 1:99.Google Scholar
  18. Kahane, H., 1980, “Logic and Contemporary Rhetoric: The Use of Reason in Everyday Life,” Wadsworth, Belmont, California.Google Scholar
  19. Keely, C.B., 1982, Illegal migration, Scientific American, 3:41.CrossRefGoogle Scholar
  20. Kimble, G.R., 1978, “How to Use (and Misuse) Statistics,” Prentice-Hall, Englewood Cliffs, New Jersey.Google Scholar
  21. Levin, G., 1982, “Writing and Logic,” Harcourt Brace Jovanovich, New York.Google Scholar
  22. Matlack, W.F., 1980, “Statistics for Public Policy and Management,” Duxbury Press, North Scituate, Massachusetts.Google Scholar
  23. Moore, D.S., 1985, “Statistics: Concepts and Controversies,” W.H. Freeman and Company, New York.Google Scholar
  24. Mosteller, F., 1977, Assessing Unknown Numbers: Order of Magnitude estimation in: “Statistics and Public Policy,” W. Fairley and F. Mosteller, eds., Addison-Wesley, Reading, Massachusetts.Google Scholar
  25. Mueller, J.H., Schuessler, K.F., and Costner, H.L., 1977, “Statistical Reasoning in Sociology,” Houghton Mifflin, Boston.Google Scholar
  26. Reuter, P., 1984, The (continued) vitality of mythical numbers, Public Interest, 75:135.Google Scholar
  27. Schuster, J.M.D., 1986, Making compromises to make comparisons in cross-national arts policy research, Journal of Cultural Economics, 11:2.Google Scholar
  28. Singer, M., 1971, The vitality of mythical numbers, Public Interest, 23:3.Google Scholar
  29. Smith, G., 1985, “Statistical Reasoning,” Allyn & Bacon, Boston.Google Scholar
  30. Toulmin, S., Rieke, R., and Janik, A., 1984, “An Introduction to Reasoning,” Macmillan, New York.Google Scholar
  31. Tversky, A., and Kahneman, D., 1977, Judgement under uncertainty: Heuristics and biases, in: “Statistics and Public Policy,” W. Fairley and F. Mosteller, eds., Addison-Wesley, Reading, Massachusetts.Google Scholar
  32. United Nations, 1984a, “Compiling Social Indicators on the Situation of Women,” Studies in Methods, Series F, No. 32, Publication No. E.84.XVII.2, United Nations, New York.Google Scholar
  33. United Nations, 1984b, “Improving Concepts and Methods for Statistics and Indicators on the Situation of Women,” Studies in Methods, Series F, No. 33, Publication No. E.84.XVII.3, United Nations, New York.Google Scholar
  34. Weiss, R.S., 1968, “Statistics in Social Research: An Introduction,” John Wiley & Sons, New York.Google Scholar
  35. Willemain, T.R., 1980, “Statistical Methods for Planners,” MIT Press, Cambridge, Massachusetts.Google Scholar
  36. Winkler, R.L., and Hays, W.L., 1975, “Statistics: Probability, Inference, and Decision,” Holt, Rinehart and Winston, New York.Google Scholar
  37. Zeisel, H., 1968, “Say It With Figures,” Harper & Row, New York.Google Scholar

Copyright information

© Plenum Press, New York 1990

Authors and Affiliations

  • J. Mark Davidson Schuster
    • 1
  1. 1.Massachusetts Institute of TechnologyUSA

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