Weblinks http://www:stat.sc.edu/_west/applets/chisqdemo1.html http://2012books.lardbucket.org/books/beginning-statistics/s15-chi-square-tests-and-f- tests.html www.psypress.com/spss-made-simple Suggested Readings Siegel, S. & Castellan, N.J. (1988). Non Parametric Statistics for the Behavioral Sciences (2nd edn.). McGraw Hill Book Company: New York. Clark- Carter, D. (2010). Quantitative psychological research: a student’s handbook (3rd edn.). Psychology Press: New York. Myers, J.L. & Well, A.D. (1991). Research Design and Statistical analysis. New York: Harper Collins. Agresti, A. 91996). An introduction to categorical data analysis. New York: Wiley. PSYCHOLOGY PAPER No.2 : Quantitative Methods MODULE No. 15: Non parametric test: chi square test of contingencies Zimmerman, D. & Zumbo, B.D. (1993). The relative power of parametric and non- parametric statistics. In G. Karen & C. Lewis (eds.), A handbook for data analysis in behavioral sciences: Methodological issues (pp. 481- 517). Hillsdale, NJ: Lawrence Earlbaum Associates, Inc. Field, A. (2005). Discovering statistics using SPSS (2nd ed.). London: Sage. Biographic Sketch Description 1894 Karl Pearson(1857-1936) was the first person to use the term “standard deviation” in one of his lectures. contributed to statistical studies by discovering Chi square. Founded statistical laboratory in 1911 in England. http://www.swlearning.com R.A. Fisher (1890- 1962) Father of modern statistics was educated at Harrow and Cambridge where he excelled in mathematics. He later became interested in theory of errors and ultimately explored statistical problems like: designing of experiments, analysis of variance. He developed methods suitable for small samples and discovered precise distributions of many sample statistics. The chi square test of contingency is another contribution made by R. Fisher to the field of statistics. PSYCHOLOGY PAPER No.2 : Quantitative Methods MODULE No. 15: Non parametric test: chi square test of contingencies Glossary C Chi square: the chi square is a non-parametric test used for inferential analysis to evaluate the relationship between data obtained in nominal scale. D Degrees of freedom: represented as df. It is the number of observations that are free to vary in a distribution with known mean. E Experimental group: that group of subjects in a study which receives non- zero levels of independent variable. F Frequency: the number of times a particular value or the range of values of a variable occurs in a set of data. N Nominal scale: scale of measurement that categorizes the cases into two or more distinct categories. It is a qualitative scale that provides the least information. Non parametric statistics: that set of statistical techniques which do not rely on assumptions about the population underlying a sample. P Power: the ability of a statistic to detect an effect of a variable when one is actually present. Did You Know? Phi and Cramer’s V are two other non-parametric tests that attempt to study the association between categorical variable in 2X 2 contingency table (phi is used) when there are more than two categories then cramer’s V is suitable. Both the tests use chi square test of contingencies. Yate’s Continuity Correction: the basic rule of thumb is that no expected frequency in the 2X2 contingency table should be less than 5. But in a large sample the expected frequency should be greater than 1 and no more than 20% should have the count of less than 5. PSYCHOLOGY PAPER No.2 : Quantitative Methods MODULE No. 15: Non parametric test: chi square test of contingencies .