1. A batch of n resistors have an average of 101.5 Ohms. Assuming a population sample variance of 25. We are interested to see whether the population mean is 100 Ohms at a level of significant 0.05 (meaning that our criterion for drawing conclusion from p-value is based on 0.05). The hypothesis testing is as follows a) Ho: µ = 100 versus H1:µ # 100. For n = 100, compute the p-value and draw a conclusion for our test. b) Ho:µ 2 100 versus H,: µ < 100. For n 100, compute the p-value and draw a conclusion for our test. c) Ho: H = 100 versus H1:µ # 100. For n = 10, compute the p-value and draw a conclusion for our test.

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1.
A batch of n resistors have an average of 101.5 Ohms. Assuming a
population sample variance of 25. We are interested to see whether the population
mean is 100 Ohms at a level of significant 0.05 (meaning that our criterion for drawing
conclusion from p-value is based on 0.05). The hypothesis testing is as follows
a) Ho: u = 100 versus H1: µ + 100.
For n =
100, compute the p-value and draw a conclusion for our test.
b) Ho: µ 2 100 versus H,: µ < 100.
For n = 100, compute the p-value and draw a conclusion for our test.
c) Ho: µ = 100 versus H1:µ 100.
For n =
10, compute the p-value and draw a conclusion for our test.
Transcribed Image Text:1. A batch of n resistors have an average of 101.5 Ohms. Assuming a population sample variance of 25. We are interested to see whether the population mean is 100 Ohms at a level of significant 0.05 (meaning that our criterion for drawing conclusion from p-value is based on 0.05). The hypothesis testing is as follows a) Ho: u = 100 versus H1: µ + 100. For n = 100, compute the p-value and draw a conclusion for our test. b) Ho: µ 2 100 versus H,: µ < 100. For n = 100, compute the p-value and draw a conclusion for our test. c) Ho: µ = 100 versus H1:µ 100. For n = 10, compute the p-value and draw a conclusion for our test.
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