week 101 Test on Pairs of Means – Case I Suppose are iid independent of that are iid. Further, suppose that n 1 and n 2 are large or that are known. We are interested in testing H 0 : μ x = μ y versus a one sided or a two sided alternative… Then,…

week 102 Test on Pairs of Means – Case II Suppose are iid independent of that are iid. Further, suppose that n 1 and n 2 are small and that are unknown but we assume they are equal to σ 2. We are interested in testing H 0 : μ x - μ y = δ versus a one sided or a two sided alternative… Then,…

week 103 Example The strength of concrete depends, to some extent, on the method used for drying it. Two drying methods were tested on independently specimens yielding the following results… We can assume that the strength of concrete using each of these methods follows a normal distribution with the same variance. Do the methods appear to produce concrete with different mean strength? Use α = 0.05.

week 104 Test on Pairs of Means – Case III Suppose are iid with E(X i ) = µ x and Var(X i ) = σ x independent of that are iid with E(Y i ) = µ y and Var(Y i ) = σ y Further, suppose that n 1 and n 2 are both large. We are interested in testing H 0 : μ x - μ y = δ versus a one sided or a two sided alternative… Then,…

week 105 Test on Two Proportions Suppose are iid Bernoulli(θ 1 ) independent of that are iid Bernoulli(θ 2 ). Further, suppose that n 1 and n 2 are large. We are interested in testing H 0 : θ 1 = θ 2 versus a one sided or a two sided alternative… Then,…

week 106 Example

week 107 Paired Observations In a matched pairs study, subjects are matched in pairs and the outcomes are compared within each matched pair. The experimenter can toss a coin to assign two treatment to the two subjects in each pair. One situation calling for match pairs is when observations are taken on the same subjects, under different conditions. A match pairs analysis is needed when there are two measurements or observations on each individual and we want to examine the difference. This corresponds to the case where the samples are not independent. For each individual (pair), we find the difference d between the measurements from that pair. Then we treat the d i as one sample and use the one sample t test and confidence interval to estimate and test the difference between the treatments effect.

week 108 Example Seneca College offers summer courses in English. A group of 20 students were given the TOFEL test before the course and after the course. The results are summarized in the next slide. Find a 95% CI for the average improvement in the TOFEL score. Test whether attending the course improve the performances on the TOFEL.

week 109 Data Display Row Student Pretest Posttest improvement

week 1010 One sample t confidence interval for the improvement T-Test of the Mean Test of mu = vs mu > Variable N Mean StDev SE Mean T P improvemt MINITAB commands for the paired t-test Stat > Basic Statistics > Paired t Paired T-Test and Confidence Interval Paired T for Posttest – Pretest N Mean StDev SE Mean Posttest Pretest Difference % CI for mean difference: (-0.049, 2.949) T-Test of mean difference=0 (vs > 0): T-Value = 2.02 P-Value = 0.029

week 1011 Character Stem-and-Leaf Display Stem-and-leaf of improvement N = 20 Leaf Unit = (7)

week 1012 Test for a Single Variance Suppose X 1, …, X n is a random sample from a N(μ, σ 2 ) distribution. We are interested in testing versus a one sided or a two sided alternative… Then…

week 1013 Test on Pairs of Variances Suppose are iid independent of that are iid. We are interested in testing versus a one sided or a two sided alternative… Then…

week 1014 Example