Chi Square

- analysis sheet from last time: authorisation intervals doctrine intervals take on the usual pulp: logical p arentage = 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 testing Of course, any of the dominance intervals on the previous slide go off be turned into hypothesis tests by computing tobt = (observed expected)/SE, and comparing 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, median, & mode Ra nge, variance, & standard deviation Inferential self-reliance intervals Hypothesis testing 1 Two categories of inferential statistics parametric What weve done so far parametric statistics Limited to three-figure sorts of dependent variables (as opposed to, e.g.

, categorical or ordinal variables) contain dependent variable scores are normally distributed, or at least their means are approximately normal. there exist virtually parametric statistical procedures that assume whatever other, non-normal distribution, but mostly a normal distribution is assumed. The full general point: parametric statistics operate with some assumed form for the distribution of t he data. Nonparametric What well talk ! about in this yack away 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 nonparametric. Parametric procedures are robust...If you involve to get a full essay, order it on our website: OrderEssay.net

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