MATH 2300: Statistical Methods
Chapter 2
Section 2.1 What are the types of Data
Variable
A
variable
is any characteristic that is observed for the subjects in a study.
The data values that are observed for a variable are referred to as the
observations.
Categorical and Quantitative variables
•
Categorical:
A variable is categorical if each observation belongs to one of a set of categories
•
Quantitative:
A variable is quantitative if observations on it take numerical values that represent different
magnitudes of the variable.
Ex 7:
Examples for categorical variables
Gender:
male, female
Hair color:
blond, brown, red, black
Blood type:
A, B, AB, O
Examples for quantitative variables
Age
Height
Number of children for a family
Discrete and Continuous variables
A quantitative variable could be either
discrete
or
continuous
.
•
Discrete:
A quantitative variable is discrete if it’s possible values form a set of separate numbers such as
0,1,2,3,….
•
Continuous:
A quantitative variable is continuous if its possible values form an interval
Ex 8:
Examples for discrete variables
Number of students in a class:
Only counting numbers
Height of a pile of bricks of height ½” each:
Only multiples of ½”
Examples for continuous variables
Height of a person:
Can take any value in a some interval (say from 1’ to 9’)
Temperature of Lubbock:
Can take any value in some interval (25 to 110)
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Summarizing data using tables and graph
The methods used for summarizing and ana
Proportion and Percentages (relative frequ
•
Proportion
of the observations tha
g
G±²³´²µ¶· ¸¶¹´µº» ¹G ¹¼½²±¾¿
º¹º¿À µ´Á¼²± ¹G ¹
•
Percentage
of the observations tha
g
G±²³´²µ¶· ¸¶¹´µº» ¹G ¹¼½²±¾¿
º¹º¿À µ´Á¼²± ¹G ¹
Proportions and percentages are also called
Frequency Table
A
frequency table
is a listing of possible val
Ex 9:
A campus press polled a sample of 300 und
change in a dormitory regulation. Summary
Response
Frequen
Support
Neutral
Oppose
Total
Categorical
variables
alyzing data depend on the type of the variable.
uencies)
at fall in a certain category
¿ºÂ¹µ½ Âµ ºÃ¿º ¶¿º²Ä¹±·
¹¼½²±¾¿ºÂ¹µ½
at fall in a certain category =
Proportion
* 100
¿ºÂ¹µ½ Âµ ºÃ¿º ¶¿º²Ä¹±·
¹¼½²±¾¿ºÂ¹µ½
Å uUU
d
relative frequencies
.
lues for a variable, together with the number of obs
dergraduate students in order to study students’ atti
y of results of an opinion poll is as follows.
ncy
Proportion
Percentage
150
=150/300 = 0.5
5
50
= 50/300 = 0.167
16.
100
= 100/300 = 0.333
33.
300
1
10
Variables
Quantitativ
variables
Discrete
varaibles
servations for each value.
titude towards a proposed
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '08
 Staff
 Math, Statistics, StemAndLeaf Plots, Quartile

Click to edit the document details