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Material Type: Exam; Professor: Pathak; Class: Statistical Methods; Subject: Statistics and Probability; University: Michigan State University; Term: Spring 2009;
Typology: Exams
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STT 201, Sections 7--11 UNIT 4 Example Multiple Choice Questions 1-4. For each of the following testing situations, give the p-value of the observed test statistic. Pick the closest.
13-15. A study is undertaken to compare the distributions of weights of adult perch in Lake Michigan, Lake Huron and Lake Erie. Random samples of sizes 100, 200, 300 respectively are obtained from these lakes and each sample fish is weighed. Weight is recorded in four categories. The sample data are shown below. Weight Category Under 8 ounces 8 – 12 ounces 12 – 16 ounces 16 ounces or more Total Michigan 10 40 40 10 100 Huron 45 65 60 30 200 Erie 65 135 80 20 300 Total 120 240 180 60 600
Cost = 66.8 – 0.370age + 0.00583pages Predictor Coef SE Coef T p Constant 66.847 2.279 29.33 0. age -0.36963 0.05262 ______ _____ pages 0.005834 0.004334 ______ _____ s=4.279 R-sq = _____ R-sq(adj) = _______ Analysis of Variance SOURCE DF SS MS F p Regression 2 _____ 529.29 30.75 0. Error 50 860.71 17. Total 52 1919.
CI for ^ d : n s d t * d , where t *is based on n-1 degrees of freedom. Test statistic: n s d t d obs ^ , where t^ obs is based on n-1 degrees of freedom. METHODS BASED ON TWO INDEPENDENT SAMPLES Estimators: y 1 ^ y 2 for^ 1 ^ 2 , s 1 for^ 1 , s 2 for^ 2 ; p 1 - p 2 for^ 1 ^ 2 CI's (for 1 - 2 or 1 - 2 ) 2 2 2 1
n p p n p p p p z
where isbasedon thesmallerof 1 1 and 2 1 (conservativeapproach to d.f.).
2 2 2 1 2
where, with theconservativeapproach, isbasedonsmallerofn 1 - 1 andn 2 - 1 degreesof freedom. 2 2 2 1 2 1 1 2 obs t obs n s n s y y t
values. For large n, use the test statistic ^2 obs = (Oj - Ej)^2 / Ej where the summation is over all k cells and Ej=njo , j=1,…k. If Ho is true, then the test statistic has approximately a ^2 distribution with k-1 df.
One classification variable has r levels and the other has c levels. The observed frequencies Oj are in a contingency table with r rows and c columns. For large n, use the test statistic ^2 obs = (Oj - Ej)^2 / Ej where the expected cell frequencies are Ej = (row total)(column total)/(grand total) and the summation is over all rc cells of the contingency table. If Ho is true, then the test statistic has approximately a ^2 distribution with (r – 1)(c – 1) df.
v. Ha: Not so. There are r populations and c levels for the classification variable. The observed frequencies Oj are in a contingency table with r rows and c columns. For large n, use the test statistic ^2 obs = (Oj - Ej)^2 / Ej where the expected cell frequencies are Ej = (row total)(column total)/(grand total) and the summation is over all rc cells of the contingency table. If Ho is true, then the test statistic has approximately a ^2 distribution with (r – 1) (c – 1) df. 2 2 2 1
n p p n p p p p z