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?
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Hypothesis Testing using Confidence Interval Approach; Author: BUM2413 Applied Statistics UMP;https://www.youtube.com/watch?v=Hq1l3e9pLyY;License: Standard YouTube License, CC-BY
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