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, 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. (-5[1])The formula “rows minus one times columns (10[1])minus (10[1])one” gives the value of a parameter (10[1])when computing a test (-5[1])statistic converging (10[1])to this distribution, which sums values of “observed minus expected (10[1])squared, (-5[1])all over expected” (-5[1])for each entry in a contingency table. For 10 points, (10[1])what distribution names a large-sample hypothesis test for goodness-of-fit (-5[1])or independence? ■END■ (10[4]0[2])