Chi Square

- analysis sheet from last time: authorisation intervals confidence intervals take on the usual stamp: logical bloodline = statistic ± tcrit SE(statistic) parameter a b y (mean) ynew (individual) SE se · sqrt(1/N + mx2/ssxx) se/sqrt(ssxx) se · sqrt(1/N + (xo mx)2/ssxx) se · sqrt(1/N + (xnew mx)2/ssxx + 1) Summary sheet from last time: Hypothesis interrogatory Of course, any of the dominance intervals on the previous slide cig artte be turned into hypothesis rivulets by computing tobt = (observed expected)/SE, and examine with tcrit. Testing H0: ?=0: tobt = r·sqrt(N-2)/sqrt(1-r2) Comp are with tcrit for N-2 degrees of freedom. Testing H0: ?=?o: Need to practice session a different test statistic for this. Where tcrit is with N-2 degrees of freedom, and se = sqrt(?(yi yi)2/(N-2)) = sqrt((ssyy b·ssxy)/(n-2)) Statistics Chi-square tests and non­ parametric statistics 9.07 4/13/2004 descriptive Graphs Frequency distributions Mean, medi an, & mode Range, variance, & standard deviation Inferential confidence intervals Hypothesis testing 1 Two categories of inferential statistics parametric What weve done so far parametric statistics Limited to decimal sorts of dependent variables (as opposed to, e.g., categorical or ordinal variables) lease dependent variable scores are normally distributed, or at least their means are approximately normal. on that point exist virtually parametric statistical procedures that assume rough other, non-normal distribution, but mostly a normal distribution is assumed. The ordinary point: parametric statistics operate with some assumed form for the distribution of the data. Nonparametric What well talk about in this confab Sometimes require that population variances are equal Parametric statistics scoop to design a study that allows you to use parametric procedures when possible, because parametric statistics are more powerful than nonpa rametric. Parametric procedures are robust.! ..If you involve to get a full essay, order it on our website: OrderEssay.net

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