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Statistics in Water Resources, Lecture 6 • Key theme – T-distribution for distributions where standard deviation is unknown – Hypothesis testing – Comparing two sets of data to see if they are different • Reading: Helsel and Hirsch, Chapter 6 Matched Pair Tests Chi-Square Distribution http://en.wikipedia.org/wiki/Chi-square_distribution t-, z and ChiSquare Source: http://en.wikipedia.org/wiki/Student's_t-distribution Normal and t-distributions Normal t-dist for ν = 1 t-dist for ν = 5 t-dist for ν = 2 t-dist for ν = 10 t-dist for ν = 3 t-dist for ν = 30 Standard Normal and Student - t • Standard Normal z – X1, … , Xn are independently distributed (μ,σ), and – then is normally distributed with mean 0 and std dev 1 • Student’s t-distribution – Applies to the case where the true standard deviation σ is unknown and is replaced by its sample estimate Sn p-value is the probability of obtaining the value of the test-statistic if the null hypothesis (Ho) is true If p-value is very small (<0.05 or 0.025) then reject Ho If p-value is larger than α then do not reject Ho 6 One-sided test Two-sided test Helsel and Hirsch p.120 Box and Whisker Plots of the N data Precipitation Water Quality at two sites Ranked Precipitation Quality Data Mean concentration is nearly the same but ranks suggest residential concentration is smaller. Is this so? Wilcoxon Rank Sum Test Helsel and Hirsch p. 462 This is < 0.05 for a one-sided test, thus reject Ho and say residential concentration is lower than industrial Test sum of higher ranks p-value in middle is for P(Wrs > X) or P(Wrs < X*) for m = n = 10 Note that the sum of n = 1, 2, …. 20 = 210 and X + X* = 210 in all cases in this table. p-value is 0.024 for Rank sum of 78.5 Test sum of lower ranks