Question

The bad debt ratio for a financial institution is defined to be the dollar value of loans defaulted divided by the total dollar value of all loans made. Suppose that a random sample of 7 Ohio banks is selected and that the bad debt ratios (written as percentages) for these banks are 8%, 7%, 8%, 6%, 896, 796, and 596. Click here for the Excel Data File (a-1) Banking officials claim that the mean bad debt ratio for all Midwestern banks is 3.5 percent and that the mean bad debt ratio for Ohio banks is higher. Set up the null and alternative hypotheses needed to attempt to provide evidence supporting the claim that the mean bad debt ratio for Ohio banks exceeds 3.5 percent (Round your answers to 1 decimal place. Omit the % sign in your response.) 3.51% versus Haup 35 % (a-2) Discuss the meanings of a Type I error and a Type Il error in this situation. Type I: Conclude the mean bad debt ratio is> 3.5% when it actually is not. 3.5% when it actually is not. Type I1: Conclude the mean bad debt ratio is S (b) Assuming that bad debt ratios for Ohio banks are approximately normally distributed, use critical values and the given sample information to test the hypotheses you set up in part a by setting a equal to .01. Also, interpret the p-value of 0.0002 for the test. (Round your answers to 3 decimal places.) t 01 Since t.01 vt reject

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b)

(X-X) 1.000 0.000 1.000 -1.000 1.000 0.000 2.000 (x-x)2 1.0000 0.0000 1.0000 1.0000 1.0000 0.0000 4.0000 8.0000 1.333 1.155 S.No 8.00 7.00 8.00 6.00 8.00 7.00 5.00 49 2 4 Ex 7.000 -(x-x)/(n-1)- null hypothesis Alternate Hypothesis 3.5 3.5 for 0.01 level with right tailed test and n-1-6 degree of freedom, critical value of t- Decision rule: 3.143 reject Ho if test statistic t 3.143 population mean sample mean sample size sample std deviation 3.5 7.000 7.00 1.155 x= n- standard errror of meanS&-s/Vn- 0.436 test statistic t 8.020

from above t =8.020

t0.01 =3.143

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