A power company wants to see if the average amount of current passing through a series of connections is larger than 30 milliamperes (mA). They randomly select 35 of the connections and find a sample average current of 32 mA, with a sample standard deviation of 5 mA. Run a hypothesis test with α = 0.05 to see if the population average current is more than 30 mA. 10 years ago, the census bureau estimated the average number of U.S. citizens residing in rural counties to be 75,000. Now, they wish to see if the average has changed. They take a sample of 31 counties across the U.S. From the counties sampled, the average number of residents was 77,000, with a standard deviation of 5700. Using a significance level of α = 0.05, run a test to see if the average has changed over the past decade. Engineers in a bottle manufacturing facility want to see if the average width of the bottle wall is less than 0.1 cm. To test this, they randomly sample 500 bottles and measure the wall width. The sample average width is 0.099 cm. They also know from previous experience that the standard deviation in wall widths for the population is 0.01 cm. Run a hypothesis test with α = 0.05 to see if the population average wall width is less than 0.1 cm.
A power company wants to see if the average amount of current passing through a series of connections is larger than 30 milliamperes (mA). They randomly select 35 of the connections and find a sample average current of 32 mA, with a sample standard deviation of 5 mA. Run a hypothesis test with α = 0.05 to see if the population average current is more than 30 mA.
10 years ago, the census bureau estimated the average number of U.S. citizens residing in rural counties to be 75,000. Now, they wish to see if the average has changed. They take a sample of 31 counties across the U.S. From the counties sampled, the average number of residents was 77,000, with a standard deviation of 5700. Using a significance level of α = 0.05, run a test to see if the average has changed over the past decade.
Engineers in a bottle manufacturing facility want to see if the average width of the bottle wall is less than 0.1 cm. To test this, they randomly sample 500 bottles and measure the wall width. The sample average width is 0.099 cm. They also know from previous experience that the standard deviation in wall widths for the population is 0.01 cm. Run a hypothesis test with α = 0.05 to see if the population average wall width is less than 0.1 cm.
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