9-71. A type 1 statistical error is when a true null hypothesis is rejected and can also be referred
to as a false positive. An example of this would be if a manufacturing company believes that one
of their products may be unsafe so they discontinue the product, but the product was safe. A type
2 statistical error is when a false null hypothesis has failed to be rejected and can also be referred
to as a false negative. An example of this would be if the same manufacturing company believes
one of their products is safe and continues producing it when the product is unsafe
9-73. If the population proportion equals zero, then there is no part of the population that falls
within those parameters and therefore no information (mean, standard deviation, etc.) regarding
the population or any samples that could come from it. Any hypothesis test calculations would
have an outcome of zero or an invalid outcome. The best way to perform this type of hypothesis
test would be to perform the hypothesis test for the rest of the population on take the inverse to
account for the proportion that is equal to zero.
9-97.Ho=5 HA>5
Can Inland support its advertising claim?
Given 0=0.05, the test statistic is Z (0.05) = 1.645
Since Z=-0.93 is less than Z (0.05) =1.645, we fail to reject the null hypothesis. So, we cannot
conclude that Inland Empire can support its claim.
Which type of hypothesis error would the consumer group be most interested in controlling?
Type 1 Error
Which type of hypothesis test error would the company be most interested in controlling?
Type 2 Error