A four pack of batteries cost 5.16 at this price what is the cost of
1.29 for 1 pack
The Food and Drug Administration (FDA) is a U.S. government agency that regulates (you guessed it) food and drugs for consumer safety. One thing the FDA regulates is the allowable insect parts in various foods. You may be surprised to know that much of the processed food we eat contains insect parts. An example is flour. When wheat is ground into flour, insects that were in the wheat are ground up as well. The mean number of insect parts allowed in 100 grams (about 3 ounces) of wheat flour is 75. If the FDA finds more than this number, they conduct further tests to determine if the flour is too contaminated by insect parts to be fit for human consumption. The null hypothesis is that the mean number of insect parts per 100 grams is 75. The alternative hypothesis is that the mean number of insect parts per 100 grams is greater than 75. Is the following a Type I error or a Type II error or neither? The test fails to show that the mean number of insect parts is greater than 75 per 100 grams when it is. Group of answer choices Type I error Type II error
Type II error
Let's remember the definition of Type I error and Type II error:
A type I error is the rejection of a true null hypothesis, this means that we would get a "false positive" with this error.
A type II error is the non rejection of a not true null hypothesis, this error would give us a "false negative".
In this problem the mean number of insect parts per 100 grams is 75. However, the test fails to show that this number is greater than 75 when it is, this means that the test is not detecting these insect parts and therefore is giving a "false negative"
Thus, this is a Type II error.
This situation is an example of a Type II error. This occurs when the test fails to reject the null hypothesis when it should be rejected. In this context, it means the test was unable to detect the actual average content of insect parts is higher than the allowable limit.
The situation presented constitutes a Type II error in the field of hypothesis testing in statistics. A Type II error occurs when the tester fails to reject the null hypothesis when it should be rejected. In this context, it means the test failed to show that the mean number of insect parts per 100 grams is greater than 75, when in fact, it is. This can potentially mean allowing more contaminated flour into the market because the test did not pick up on the true mean being higher than 75 insect parts per 100 grams.
In general, you solve questions of cancavity by looking at the second derivative. It will be negative where the function is concave downward. (It will be positive for concave upward, and zero at points of inflection.)
I find it convenient to get guidance from a graphing calculator.
f(x) is concave downard on the interval (-∞, 2).
_____ The derivative is .. f'(x) = e^-x -x*e^-x The second derivative is .. f''(x) = -e^-x -(e^-x -x*e^-x) .. = (x -2)*e^-x This will be negative for x < 2.