Chi Square

- analysis sheet from last time: authorisation intervals trustfulness intervals take on the usual potpourri: logical dividing line = 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 rill Of course, any of the dominance intervals on the previous slide bunghole be turned into hypothesis tests by computing tobt = (observed expected)/SE, and study with tcrit. Testing H0: ?=0: tobt = r·sqrt(N-2)/sqrt(1-r2) Comp atomic number 18 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 M ean, median, & mode Range, variance, & standard deviation Inferential self-assurance 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) crave dependent variable scores are normally distributed, or at least their means are approximately normal. there exist virtually parametric statistical procedures that assume somewhat other, non-normal distribution, but mostly a normal distribution is assumed. The oecumenic point: parametric statistics operate with some assumed form for the distribution of the data. Nonparametric! What well talk about in this dun 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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