 Chapter Chapter 1: The Role of Statistics and the Data Analysis Process
 Chapter Chapter 10: Hypothesis Testing Using a Single Sample
 Chapter Chapter 11: Comparing Two Populations or Treatments
 Chapter Chapter 12: The Analysis of Categorical Data and GoodnessofFit Tests
 Chapter Chapter 13: Simple Linear Regression and Correlation: Inferential Methods
 Chapter Chapter 14: Multiple Regression Analysis
 Chapter Chapter 15: Analysis of Variance
 Chapter Chapter 2: Collecting Data Sensibly
 Chapter Chapter 3: Graphical Methods for Describing Data
 Chapter Chapter 4: Numerical Methods for Describing Data
 Chapter Chapter 5: Summarizing Bivariate Data
 Chapter Chapter 6: Probability
 Chapter Chapter 7: Random Variables and Probability Distributions
 Chapter Chapter 8: Sampling Variability and Sampling Distributions
 Chapter Chapter 9: Estimation Using a Single Sample
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ISBN: 9780495118732
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Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

Bivariate distribution
The joint probability distribution of two random variables.

Bivariate normal distribution
The joint distribution of two normal random variables

Causal variable
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

Curvilinear regression
An expression sometimes used for nonlinear regression models or polynomial regression models.

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Dispersion
The amount of variability exhibited by data

Error mean square
The error sum of squares divided by its number of degrees of freedom.

Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

Event
A subset of a sample space.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .
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