Degrees of freedom (df): The number of independent units of information in a sample used in the estimation of a parameter or calculation of a statistic. In the simplest example of a 2×2 table if the marginal totals are fixed only one of the four cell frequencies is free to vary and the others will be dependent on this value not to alter the marginal totals. Thus the df is only 1. Similarly it can easily be worked out that in a contingency table with r rows and c columns the df = (r-1)(c-1). In parametric tests the idea is slightly different that the n bits of data have n degrees of freedom before we do any statistical calculations. As soon as we estimate a parameter such as the mean we use up one of the df which was initially present. This is why in most formulas the df is (n-1). In the case of a two-sample t-test with n1 and n2 observations to do the test we calculate both means. Thus the df = (n1 + n2 – 2). In linear regression when the linear equation y =

Tags: Absolute Risk, Addition Rule, Adjusted Odd Ratio, Age-Standardized Rate, ANOVA, ANOVCA, Arithmetic Mean, Association, asymptotic, Asymptotically, Basic statistics tests, Correlation, Data Analysis, methods, Methods & Tests, Sample Data, SPSS Analysis, SPSS Data, SPSS Functions, statistics, Statistics Assumptions, Statistics Functions, Statistics Methods, Statistics Results, Statistics Tests, tests

Posted on February 6th, 2012