he quality department at an electronics company has noted that, historically, 91% of the units of a specific product pass a test operation, 6% fail the test but are able to be repaired, and 3% fail the test and need to be scrapped. Due to recent process improvements, the quality department would like to test if the rates have changed. A recent sample of 500 parts revealed that 473 parts passed the test, 20 parts failed the test but were repairable, and 7 parts failed the test and were scrapped. (You may find it useful to reference the appropriate table: chi-square table or table) a. Choose the appropriate alternative hypothesis for the test.

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The quality department at an electronics company has noted that, historically, 91% of the units of a specific product pass a test operation, 6% fail the test but are able to be repaired, and 3% fail the test and need to be scrapped. Due to recent process improvements, the quality department would like to test if the rates have changed. A recent sample of 500 parts revealed that 473 parts passed the test, 20 parts failed the test but were repairable, and 7 parts failed the test and were scrapped. (You may find it useful to reference the appropriate table: chi-square table or table)
a. Choose the appropriate alternative hypothesis for the test.

The quality department at an electronics company has noted that, historically, 91% of the units of a specific product pass a test
operation, 6% fail the test but are able to be repaired, and 3% fail the test and need to be scrapped. Due to recent process
improvements, the quality department would like to test if the rates have changed. A recent sample of 500 parts revealed that 473
parts passed the test, 20 parts failed the test but were repairable, and 7 parts failed the test and were scrapped. (You may find it
useful to reference the appropriate table: chi-square table or F table)
a. Choose the appropriate alternative hypothesis for the test.
At least one of the p; (i = 1, 2, 3) differs from its hypothesized value.
O All pi (i = 1, 2, 3) values differ from its hypothesized value.
b-1. 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
b-2. Find the p-value.
0.01 ≤ p-value < 0.025
p-value < 0.01
p-value > 0.10
0.05 ≤ p-value < 0.10
O 0.025 ≤ p-value < 0.05
c-1. At the 5% significance level, what is your conclusion?
HO and conclude at the 5% significance level that at least one of the proportions have changed from the historical rates.
Transcribed Image Text:The quality department at an electronics company has noted that, historically, 91% of the units of a specific product pass a test operation, 6% fail the test but are able to be repaired, and 3% fail the test and need to be scrapped. Due to recent process improvements, the quality department would like to test if the rates have changed. A recent sample of 500 parts revealed that 473 parts passed the test, 20 parts failed the test but were repairable, and 7 parts failed the test and were scrapped. (You may find it useful to reference the appropriate table: chi-square table or F table) a. Choose the appropriate alternative hypothesis for the test. At least one of the p; (i = 1, 2, 3) differs from its hypothesized value. O All pi (i = 1, 2, 3) values differ from its hypothesized value. b-1. 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 b-2. Find the p-value. 0.01 ≤ p-value < 0.025 p-value < 0.01 p-value > 0.10 0.05 ≤ p-value < 0.10 O 0.025 ≤ p-value < 0.05 c-1. At the 5% significance level, what is your conclusion? HO and conclude at the 5% significance level that at least one of the proportions have changed from the historical rates.
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