The quality- control manager at a light emitting diode (LED) factory needs to determine whether the mean life of a large shipment of LEDs is equal to 50,000 hours. The population standard deviation is 1,500 hours. A random sample of 64 LEDs indicates a sample mean life of 49,875 hours. a. At the 0.05 level of significance, is there evidence that the mean life is different from 50,000 hours? b. Compute the p -value and interpret its meaning. c. Construct a 95 % confidence interval estimate of the population mean life of the LEDs. d. Compare the results of (a) and (c). What conclusions do you reach?
The quality- control manager at a light emitting diode (LED) factory needs to determine whether the mean life of a large shipment of LEDs is equal to 50,000 hours. The population standard deviation is 1,500 hours. A random sample of 64 LEDs indicates a sample mean life of 49,875 hours. a. At the 0.05 level of significance, is there evidence that the mean life is different from 50,000 hours? b. Compute the p -value and interpret its meaning. c. Construct a 95 % confidence interval estimate of the population mean life of the LEDs. d. Compare the results of (a) and (c). What conclusions do you reach?
The quality- control manager at a light emitting diode (LED) factory needs to determine whether the mean life of a large shipment of LEDs is equal to 50,000 hours. The population standard deviation is 1,500 hours. A random sample of 64 LEDs indicates a sample mean life of 49,875 hours.
a. At the 0.05 level of significance, is there evidence that the mean life is different from 50,000 hours?
b. Compute the p-value and interpret its meaning.
c. Construct a
95
%
confidence interval estimate of the population mean life of the LEDs.
d. Compare the results of (a) and (c). What conclusions do you reach?
Definition Definition Method in statistics by which an observation’s uncertainty can be quantified. The main use of interval estimating is for describing a range that is made by transforming a point estimate by determining the range of values, or interval within which the population parameter is likely to fall. This range helps in measuring its precision.
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