Chapter 1
Introduction to Probability and Statistics: Describing Data with Graphs
Variables and Data
Variables: any kind of characteristic that changes (over time or over unit)
Definitions
An experimental unit is the individual or object on which a varia
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Chapter 9
LargeSample Test of Hypotheses
Parts of a Statistical Test
1. the null hypothesis H0:
 assumed to be true until we can prove otherwise
2. The alternative hypothesis, Ha:
 will be accepted as true if we can disprove H0
3. The test statistic an
Chapter 7 Sampling Distributions
Parameters are numerical descriptive measures for populations
for the normal distribution, the location and shape are described by and
for a binomial distribution consisting of n trials, the location and shape are
deter
The Normal Probability Distribution
Continuous Random Variable
continuous random variables can assume the infinitely many values corresponding to
points on a line interval
Examples:
Heights, weights
length of life of a particular product
experimental
Chapter 5
Discrete random variables take on only a finite or countably infinite number of values
Three discrete probability distributions serve as models for a large number of practical
applications:
the binomial random variable
the Poisson random var
Chapter 4
Probability
We measure how often using:
Relative Frequency = f/n
Basic Concepts
experiment: process by which an observation (or measurement) is obtained
Experiment: record an age; toss a die; record an opinion; toss two coins
simple event: t
Chapter 3
Describing Bivariate Data
When two variables are measured on a single experimental unit, the resulting data are
called bivariate data
you can describe each variable individually, and you can also explore the relationship
between the two variab
Chapter 2
Describing Data with Numerical Measures
Graphical methods may not always be sufficient for describing data
Numerical measures can be created for both populations and samples
a parameter is a numerical descriptive measure calculated for a popu