Introduction to Statistics (MAT/SST 115.03 2008S)
Primary: [Front Door] [Syllabus] [Current Outline] [R] - [Academic Honesty] [Instructions]
Groupings: [Applets] [Assignments] [Data] [Examples] [Handouts] [Labs] [Outlines] [Projects] [Readings] [Solutions]
External Links: [R Front Door] [SamR's Front Door]
You can load the data with
UOPgpa = read.csv("/home/rebelsky/Stats115/Data/UOPgpa.csv")
The column headings are ID
, Hours
, and
GPA
.
plot(UOPgpa$GPA ~ UOPgpa$Hours)
lm(UOPgpa$GPA ~ UOPgpa$Hours)
Let's add it to the scatterplot, too.
abline(lm(UOPgpa$GPA ~ UOPgpa$Hours))
r = cor(UOPgpa$GPA,UOPgpa$Hours) r^2
I'll admit that I only know how to read the standard error from R, and not how to automatically get it into a variable.
We can get more information than you'll ever need about a linear model by asking for a summary of the linear model.
summary(lm(UOPgpa$GPA ~ UOPgpa$Hours))
The line of interest gives various information about the slope
>
summary(lm(UOPgpa$GPA ~ UOPgpa$Hours))
...Estimate Std. Error t value Pr(>|t|)
...UOPgpa$Hours 0.08938 0.02771 3.226 0.00184 **
...
Although R just reported the test statistic, you should calculate it yourself just to make sure that R is correc.t
Although R just reported the p-value, you should see whether you get a similar value from the table.
Remember, you compute the confidence interval with b +/- t^{*}SE(b). You can look up the critical value in the table.
Although we used some calculations last time (to make sure that you
understood how to get residuals), you can use residuals
and lm
together to get the residuals.
res = residuals(lm(UOPgpa$GPA ~ UOPgpa$Hours))
Recall that we use hist
to produce the historgram.
hist(res)
We make normal probability plots and lines through them with
qqnorm(res, datax=T) qqline(res, datax=T)
You should be able to figure this one out, since we've been doing scatterplots lately.
You can load the data with
HousePrices = read.csv("/home/rebelsky/Stats115/Data/HousePricesAG.csv")
You should be able to figure out the rest on your own (from previous exercises).
Primary: [Front Door] [Syllabus] [Current Outline] [R] - [Academic Honesty] [Instructions]
Groupings: [Applets] [Assignments] [Data] [Examples] [Handouts] [Labs] [Outlines] [Projects] [Readings] [Solutions]
External Links: [R Front Door] [SamR's Front Door]
Copyright (c) 2007-8 Samuel A. Rebelsky.
This work is licensed under a Creative Commons
Attribution-NonCommercial 2.5 License. To view a copy of this
license, visit http://creativecommons.org/licenses/by-nc/2.5/
or send a letter to Creative Commons, 543 Howard Street, 5th Floor,
San Francisco, California, 94105, USA.