For a hypothesis test of the claim that the mean amount of sleep for adults is less than 9 hours, technology output shows that the hypothesis test has power of 0.4619 of supporting the claim that u< 9 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power, then identify the val of B and interpret that value. Tme Ciance ur lalny u recugrize unat p O B. The chance of failing to recognize that p= х Tу again. O C. The chance of recognizing that µ < 9 hours The power of a test is equal to 1-B. The symbol ß represents the probability of a YD. The chance of recognizing that u< 9 hours type Il error, that is, the probability of failing to reject the null hypothesis when it is actually false. Identify the value of ß and interpret that value. Sele OK (Round to four decimal places as needed.) O A. The value ß = indicates that there is a greater than 50% chance of failing to recognize that µ< 9 hours when in reality p=7.5 hours. O B. The value B= 0.5426 indicates that there is a less than 50% chance of failing to recognize that u<9 hours when in reality u =7.5 hours. C. The value B= 0.5883 indicates that there is a greater than 50% chance of incorrectly recognizing that µ< 9 hours when in reality µ= 9 hours. O D. The value B= indicates that there is a less than 50% chance of incorrectly recognizing that u< 9 hours when in reality p = 9 hours.
For a hypothesis test of the claim that the mean amount of sleep for adults is less than 9 hours, technology output shows that the hypothesis test has power of 0.4619 of supporting the claim that u< 9 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power, then identify the val of B and interpret that value. Tme Ciance ur lalny u recugrize unat p O B. The chance of failing to recognize that p= х Tу again. O C. The chance of recognizing that µ < 9 hours The power of a test is equal to 1-B. The symbol ß represents the probability of a YD. The chance of recognizing that u< 9 hours type Il error, that is, the probability of failing to reject the null hypothesis when it is actually false. Identify the value of ß and interpret that value. Sele OK (Round to four decimal places as needed.) O A. The value ß = indicates that there is a greater than 50% chance of failing to recognize that µ< 9 hours when in reality p=7.5 hours. O B. The value B= 0.5426 indicates that there is a less than 50% chance of failing to recognize that u<9 hours when in reality u =7.5 hours. C. The value B= 0.5883 indicates that there is a greater than 50% chance of incorrectly recognizing that µ< 9 hours when in reality µ= 9 hours. O D. The value B= indicates that there is a less than 50% chance of incorrectly recognizing that u< 9 hours when in reality p = 9 hours.
For a hypothesis test of the claim that the mean amount of sleep for adults is less than 9 hours, technology output shows that the hypothesis test has power of 0.4619 of supporting the claim that u< 9 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power, then identify the val of B and interpret that value. Tme Ciance ur lalny u recugrize unat p O B. The chance of failing to recognize that p= х Tу again. O C. The chance of recognizing that µ < 9 hours The power of a test is equal to 1-B. The symbol ß represents the probability of a YD. The chance of recognizing that u< 9 hours type Il error, that is, the probability of failing to reject the null hypothesis when it is actually false. Identify the value of ß and interpret that value. Sele OK (Round to four decimal places as needed.) O A. The value ß = indicates that there is a greater than 50% chance of failing to recognize that µ< 9 hours when in reality p=7.5 hours. O B. The value B= 0.5426 indicates that there is a less than 50% chance of failing to recognize that u<9 hours when in reality u =7.5 hours. C. The value B= 0.5883 indicates that there is a greater than 50% chance of incorrectly recognizing that µ< 9 hours when in reality µ= 9 hours. O D. The value B= indicates that there is a less than 50% chance of incorrectly recognizing that u< 9 hours when in reality p = 9 hours.
For a hypothesis test of the claim that the mean amount of sleep for adults is less than 9 hours, technology output shows that the hypothesis test has power of 0.4619 of supporting the claim that u <9 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power,
Identify the value of beta and interpret that value.
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For a hypothesis test of the claim that the mean amount of sleep for adults is less than 9 hours, technology output shows that the hypothesis test has power of
0.4619 of supporting the claim that p< 9 hours of sleep when the actual population mean is 7.5 hours of sleep. Interpret this value of the power, then identify the value
of ß and interpret that value.
Tme tiance on lalng to recugize mat ps
х Ту адain.
O B. The chance of failing to recognize that u=
O C. The chance of recognizing that µ < 9 hours The power of a test is equal to 1-B. The symbol B represents the probability of a
'D. The chance of recognizing that µ< 9 hours type Il error, that is, the probability of failing to reject the null hypothesis when it is
actually false.
Identify the value of B and interpret that value. Sele
OK
(Round to four decimal places as needed.)
O A. The value B=
indicates that there is a greater than 50% chance of failing to recognize that u< 9 hours when in reality µ = 7.5 hours.
O B. The value B = 0.5426 indicates that there is a less than 50% chance of failing to recognize that u< 9 hours when in reality u= 7.5 hours.
C. The value B= 0.5883 indicates that there is a greater than 50% chance of incorrectly recognizing that µ< 9 hours when in reality u= 9 hours.
D. The value B =
indicates that there is a less than 50% chance of incorrectly recognizing that u< 9 hours when in reality p= 9 hours.
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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