1) Use R for all parts of this problem. Use the data on heights you collected a few weeks ago. (a) Do a t-test and test the following: H0: μ = y for your recitation section vs. H1: μ ≠ y Use α = .01 (if, for example, your y = 64.72, then you would do H0: μ = 64.72) (c) now repeat but subtract 4.75 from your ¯y (so you'd do H0: μ = 59.97 ( = 64.72 − 4.75)) (d) repeat (c) but use α = .00000000001. (You do not need to (and should not) set α in R; make sure you understand why this is true!!) ← Don't ignore this!! (e) what kind of error did you probably make in part (d)? (Just write out the answer for this question). R instructions: To test, for example, that μ = 64.72, you need to give R the value of μ: t.test(height,mu = 64.72) (assuming you named your variable “height”; of course, you may have to do data$height or something similar depending on how you have your data in R). Since R gives you p-values ( = probabilities) you don't need to calculate or use t* (although R automatically prints this if you want to use it).

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter5: Inverse, Exponential, And Logarithmic Functions
Section5.6: Exponential And Logarithmic Equations
Problem 64E
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1) Use R for all parts of this problem. Use the data on heights you collected a few weeks ago.
(a) Do a t-test and test the following:
H0: μ = y for your recitation section vs. H1: μ ≠ y
Use α = .01
(if, for example, your y = 64.72, then you would do H0: μ = 64.72)
(c) now repeat but subtract 4.75 from your ¯y (so you'd do H0: μ = 59.97 ( = 64.72 − 4.75))
(d) repeat (c) but use α = .00000000001.
(You do not need to (and should not) set α in R; make sure you understand why this is true!!) ← Don't ignore
this!!
(e) what kind of error did you probably make in part (d)? (Just write out the answer for this question).
R instructions:
To test, for example, that μ = 64.72, you need to give R the value of μ:
t.test(height,mu = 64.72)
(assuming you named your variable “height”; of course, you may have to do data$height
or something similar depending on how you have your data in R).
Since R gives you p-values ( = probabilities) you don't need to calculate or use t* (although R
automatically prints this if you want to use it).

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