In the multiple parameter case, this distribution is the limit of a statistic that sandwiches an “I inverse” term between two “theta-hat minus theta-zero” terms called the Wald statistic. In a theorem about convergence to this distribution, (-5[1])one parameter equals the difference in dimension between the full parameter space and the space associated with the null hypothesis. Twice the log-likelihood ratio converges to this distribution by Wilks’ theorem. The formula “rows minus one times columns (-5[1])minus one” (10[1])gives the value of a parameter when computing a test statistic converging to this distribution, (10[1])which sums values of “observed minus expected squared, all over expected” (-5[1])for each entry in a contingency table. (-5[1])For 10 points, what distribution names a large-sample hypothesis (-5[1])test for goodness-of-fit or independence? (10[1])■END■ (10[5]0[6])