Math 214
Applied Statistics
Laboratory Project #4
Due: Monday March 19
Investigating The Central Limit Theorem
Key to understanding Inferential Statistics (and most of what follows in Mth 214) is the most
popular statistical LAW known as the Central Limit
Chi-Square - Regression Lab
In this lab we will look at how R can eliminate most of the annoying calculations involved in
(a) using Chi-Squared tests to check for homogeneity in two-way tables of catagorical data and
(b) computing correlation coecients an
I .a
A ..
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Justify answers and show all work for full credit.
NAME: Math 214 -_ Exam 3
Problem 1.
An SRS of 85 students is taken from a large university to estimate the proportion of students whose
parents bought a car for them. In the sample, the pa
t wo-sample t -tests
We learned in class how to do hypothesis tests for comparing the
means of two populations from single samples of size n1 and n2 of
these populations. This involves several steps. First we make sure
that the data are approximately norm
s ignificance tests
Imagine a data set from a hospital for post-surgery recovery times
in days. Seven patients were randomly divided into a control group of
three that received standard care, and a treatment group of four that
received a new kind of care.
u sing r to work with data
Introduction
MTH 214 has as part of its learning objectives an introduction to concepts of computing compuational literacy is the
goal, which will be taken to mean a familiarity with the following ideas: using commands to intera
c ollege age facts and figures
This project uses data collected by the National Government as part of its National Health and Nutrition Examination Survey (NHANES). There have been three such large
surveys and have proven extremely useful. Elizabeth Kolbe
Math 214
Applied Statistics
Laboratory Project #3
Due: Wednesday February 27
Part I: Using R to SIMULATE Experiments
Although Einstein said that God does not play dice, R can play dice (and cards) rather easily.
In this Lab assignment we will learn how to
Math 214
Condence Intervals
Laboratory Project #5
Due: Monday March 25
Lets look at condence intervals and hypothesis tests using some real data. Actually, we can
simulate some data and then use R to take samples, compute means and standard deviations, et
Formulas
The statistic x has
x = / n
x = ,
and if the population is normal, or n is large enough, is approximately normally distributed.
The statistic D = x1 x2 has
D = 1 2
2
If the two random samples are independent of each other then D =
2
+ 2 /n2 ). Th