Introductory Statistics

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IS: R Assignment 32

[<code class="R">R</code> Assignments]
R Assignment #32
 

General Purpose

General Purpose of these Assignments (the usual): The purpose of these R Assignments is to give you some pointed, direct practice in using R. As such, these are designed to be quick and to the point (less than 10 minutes each). They are also designed to give you a place to return if you forget how to perform some analysis in the future.

Please supply your results in the form below. Clicking on “Click to Check Your Answers” will allow you to see which as correct and which are not. When all are correct (and you can try as many time as you wish), you will be allowed to send your answers to me for credit by clicking on “Click to Email Your Results.” You only receive credit when this is submitted (with all answers correct).

This assignment is due at the start of the class period on

Wednesday, March 6, 2024.

With that being said, if this R Assignment is available, which is could be until approximately 11:59 pm (CST), then you are able to work on it.

As expected, these are graded according to the syllabus (all or nothing). Please review the appropriate section in the syllabus for more information. Also, if this is not submitted before it is due, then it counts as a zero.

Specific Purpose: This assignment continues modeling a numeric dependent variable. Here, we are using one or more numeric independent variables, hence: regression.

Slidedeck Support: The following slidedecks may be helpful for you in completing this R Assignment:

The Problems

First, run the following code. Then, answer the questions that follow. These lines of code load a particular data set and attaches it. In other words, they allow you easy access to a common data set.

source("http://rfs.kvasaheim.com/stat200.R") dt = read.csv("http://rfs.kvasaheim.com/data/HeartOfTheValleyTriathalon.csv") attach(dt)
  1. The dependent variable is the time it takes for the athlete to finish the run (RUNT). The independent variable is the time it takes for the runner to finish the swim (SWIMT). What is the slope of this model?
  2. The dependent variable is the time it takes for the athlete to finish the run (RUNT). The independent variable is the time it takes for the runner to finish the bicycling (BIKET). What is the slope of this model?
  3. The dependent variable is the time it takes for the athlete to finish the run (RUNT). There are two independent variables: the time it takes for the runner to finish the swim, and the time to finish the biking. The model should be an additive model. What is the value of the F-statistic for the model?

Finally, to receive credit for this assignment, please provide your full Knox College email address:

then click on the button here.

The Answers

Since this is past due, I can now give you the code and the answer:

Since it is now after the time this is due, I can now give you the code and the answers:

summary(lm(RUNT~SWIMT))
summary(lm(RUNT~BIKET))
summary(lm(RUNT~SWIMT + BIKET))

The answers are

0.6858
0.60536
48.02
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