Stats 024b 001
Monday
NCB 114
, Wednesday and Friday
SSC 3022
11:30-12:30
Chapter 1: Picturing Distributions with Graphs
January 7, 2008
Graphing Data
The first thing you do in any statistical analysis is you graph it: gain insight on the data
Individuals and Variables
Individuals
are the objects described by a set of data. Individuals may be people, but they
may also be animals or things (Ex. Students, M&M’s, dogs, 2 by 4’s—also called an
experimental unit or sampling unit depending on context)
Variables
are characteristics of an individual. A variable can take different values for
different individuals (Ex. Age, Height, Grades, Colour, Weight, Breed, Breaking
Strength)
Types of Variables
Quantitative
•
Something that can be counted or measured for each individual and then added,
subtracted, averaged etc, across individuals in the population
•
Examples: how tall are you, your age, your blood cholesterol level, the number of
credit cards you have
Categorical
•
Something that falls into one of several categories. What can be counted is the
count or proportion of individuals in each category
•
Examples: Your blood type (A, B, AB, O), your hair colour, your ethnicity,
whether you paid income tax last tax year or not
Distribution of the Variable
The
distribution
of the variable tells us what values it takes and how often it takes these
values.
The values of a categorical variable are labels for the categories. The
distribution of a
categorical variable
lists the categories and gives either the count or the percent of
individuals who fall into each category.
Distribution of a Categorical Variable Example
•
30% brown, 20% yellow and reds, 10% each of oranges, greens and tans
Exploring Data
1.
Begin by examining each variable by itself. Then move onto
study the relationships among the variables
2.
Begin with a graph or graphs. Then add numerical summaries of
specific aspects of the data
Bar Charts
•
Used for categorical variables
•
Gives a visual display of the relative sizes of each
category
Pie Charts
•
Used for categorical variables
Statistics 024B
1