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Therefore, we: can / cannot claim that the... A rent-to-own (RTO) agreement appe

ID: 3067042 • Letter: T

Question

Therefore, we: can / cannot claim that the...

A rent-to-own (RTO) agreement appeals to low-income and financially distressed consumers. It allows immediate access to merchandise, and by making all payments, the consumer acquires the merchandise. At the same time, goods can be returned at any point without penalty. Suppose a recent study documents that 65% of RTO contracts are returned, 30% are purchased, and the remaining 5% default. In order to test the validity of this claim, an RTO researcher looks at the transaction data of 420 RTO contracts, of which 283 are returned, 109 are purchased, and the rest defaulted. Use Table 3. a. Choose the appropriate alternative hypothesis to test whether the return, purchase, and default probabilities of RTO contracts differ from 0.65, 0.30, and 0.05, respectively OAt least one of the pi (i 1, 2, 3) differs from its hypothesized value. O All Pi (i = 1, 2, 3) values differ from its hypothesized value. b. Compute the value of the test statistic. (Round the intermediate calculations to at least 4 decimal places and final answer to 3 decimal places.) Test statistic c-1. Calculate the critical value at the 5% level of significance. (Round your answer to 3 decimal places.) Critical value c-2. Interpret the test results. (Click to select) Ho. Therefore, we Click to select) claim that the proportions of return, purchase, and default are different from 0.65, 0.30, and 0.05, respectively

Explanation / Answer

Result:

a).

option1

At least one of the pj differ from its hypothesized value.

b).

Test statistic = 143.626

C1

Critical value = 5.991

C2.

Reject, we can claim that

Goodness of Fit Test

observed

expected

O - E

(O - E)² / E

420

527.800

-107.800

22.018

283

243.600

39.400

6.373

109

40.600

68.400

115.235

812

812.000

0.000

143.626

143.626

chi-square

2

df

0.0000

p-value

Goodness of Fit Test

observed

expected

O - E

(O - E)² / E

420

527.800

-107.800

22.018

283

243.600

39.400

6.373

109

40.600

68.400

115.235

812

812.000

0.000

143.626

143.626

chi-square

2

df

0.0000

p-value

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