 121.1: Use ANOVA to test for any significant differences between the means
 121.2: What is the purpose of this study?
 121.3: Explain why separate t tests are not accepted in this situation.
 121.1: What test is used to compare three or more means?
 121.2: State three reasons why multiple t tests cannot be used to compare ...
 121.3: What are the assumptions for ANOVA?
 121.4: Define betweengroup variance and withingroup variance.
 121.5: What is the F test formula for comparing three or more means?
 121.6: State the hypotheses used in the ANOVA test.
 121.7: When there is no significant difference among three or more means, ...
 121.8: For Exercises 8 through 19, assume that all variables are normally ...
 121.9: For Exercises 8 through 19, assume that all variables are normally ...
 121.10: For Exercises 8 through 19, assume that all variables are normally ...
 121.11: For Exercises 8 through 19, assume that all variables are normally ...
 121.12: For Exercises 8 through 19, assume that all variables are normally ...
 121.13: For Exercises 8 through 19, assume that all variables are normally ...
 121.14: For Exercises 8 through 19, assume that all variables are normally ...
 121.15: For Exercises 8 through 19, assume that all variables are normally ...
 121.16: For Exercises 8 through 19, assume that all variables are normally ...
 121.17: For Exercises 8 through 19, assume that all variables are normally ...
 121.18: For Exercises 8 through 19, assume that all variables are normally ...
 121.19: For Exercises 8 through 19, assume that all variables are normally ...
Solutions for Chapter 121: Analysis of Variance
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 121: Analysis of Variance
Get Full SolutionsElementary Statistics: A Step by Step Approach was written by Patricia and is associated to the ISBN: 9780073534978. Chapter 121: Analysis of Variance includes 22 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. Since 22 problems in chapter 121: Analysis of Variance have been answered, more than 7629 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7.

Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

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

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Bivariate distribution
The joint probability distribution of two random variables.

Central composite design (CCD)
A secondorder response surface design in k variables consisting of a twolevel factorial, 2k axial runs, and one or more center points. The twolevel factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a secondorder model.

Chisquare (or chisquared) random variable
A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random 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

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

Comparative experiment
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Discrete random variable
A random variable with a inite (or countably ininite) range.

Dispersion
The amount of variability exhibited by data

Eficiency
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

Fisher’s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

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 .
I don't want to reset my password
Need help? Contact support
Having trouble accessing your account? Let us help you, contact support at +1(510) 9441054 or support@studysoup.com
Forgot password? Reset it here