Transcript Introduction

Introduction to Probability and Statistics
11th Edition
Robert J. Beaver • Barbara M. Beaver • William Mendenhall
I thank Thomson Learning Inc for granting permission to
reproduce any of the contents and ancillaries of Introduction
to Probability and Statistics (11th ed). I also thank Rebecca
Cleaver and Rae Ann Haley for assistance with formatting
and animation.
This presentation may not be reproduced in any way
without written permission.
©2004 Lorne Nelson
What is Statistics?
Statistics:
 concerns itself with the collection,
organization and analysis of data
 is a tool used by researchers in all
quantitative fields
 is used to draw general conclusions in a
wide variety of applications
Populations and Samples

POPULATION: The set of all measurements
of interest to the experimenter.
Ex: All professors at BU

SAMPLE: A subset of measurements
selected from the population of interest.
Ex: The science professors at BU
“Sample” and “Population”

Distinguish between set of objects on
which we take measurements and the
measurements themselves.
 Experimental Units: The items or
objects on which measurements are
taken (e.g., professors).
 Sample (or Population): the set of
measurements taken on the
experimental units.
Parameter
a numerical measurement on an
experimental unit describing some
characteristic of a population (e.g., mean)
Population
Parameter
Statistic
a numerical measurement describing
some characteristic of a sample (e.g.,
mean)
Sample
Statistic
Descriptive Statistics
Sometimes (but rarely) we can
enumerate the whole population
 If so, we need only use:

DESCRIPTIVE STATISTICS: Procedures
used to summarize and describe the set
of measurements.
Inferential Statistics

When we cannot enumerate the whole
population, we use:

INFERENTIAL STATISTICS: Procedures
used to draw conclusions or inferences
about the population from information
contained in the sample.
STATISTIC 
PARAMETER