Laboratory 5.pdf

# Laboratory 5.pdf - Laboratory 5 Let’s use this datatset...

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Laboratory 5 Let’s use this datatset to learn about conducting a one -sample t test. Consider the following claim: The city of Olympia, WA receives the same amount of rain per year as the average of the 70 cities represented in the precip dataset. (1a) The city of Olympia, WA averages 49.9 inches of rain per year. Find the mean amount of rain per year from the 70 cities represented in the precip dataset. Construct null and alternative hypotheses given the claim, and state whether this is a right, left, or two-tailed test. (3 points) mean amount of rain in 70 cities = 38.9 inches H : average amount of rain in Olympia = average amount of rain of 70 cities H a : average amount of rain in Olympia average amount of rain of 70 cities Two-tailed test (1b) Use R to also calculate the variance and standard deviation of the amount of rain per year in the 70 cities represented in the precip dataset. List your estimates of the variance and standard deviation below. (4 points) variance = 187.9 standard deviation = 13.7 (1c) You have previously conducted a t test by hand. Now, let’s use R to do this for us. R has a built-up function, called t.test() that we can use. To use a one-sample t test, we have to specify a few conditions in the t.test() function: t.test(precip, mu=49.9, alternative=c("X1")) where precip is the dataset you are using, mu is the mean of Olympia, WA that we are testing against the mean of the 70 cities in the precip dataset, and "X1" is the type of test you are using. X1 can be one of the following: "less" "greater"

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"two.sided" depending on if you are conducting a left-tailed test (i.e., less), right-tailed test (i.e., greater),
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