 15.7.1: In 1 and 2, (a) determine the test statistic, H, (b) determine the ...
 15.7.2: In 1 and 2, (a) determine the test statistic, H, (b) determine the ...
 15.7.3: Births by Day of Week An obstetrician knew that there were more liv...
 15.7.4: Births by Season An obstetrician wants to determine if the distribu...
 15.7.5: Corn Production The following data represent the number of corn pla...
 15.7.6: Soybean Yield The following data represent the number of pods on a ...
 15.7.7: Reaction Time In an online psychology experiment sponsored by the U...
 15.7.8: Math Scores Researchers wanted to compare math test scores of stude...
 15.7.9: Crash Data The Insurance Institute for Highway Safety conducts expe...
 15.7.10: Crash Data The Insurance Institute for Highway Safety conducts expe...
Solutions for Chapter 15.7: KRUSKALWALLIS TEST
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 15.7: KRUSKALWALLIS TEST
Get Full SolutionsSince 10 problems in chapter 15.7: KRUSKALWALLIS TEST have been answered, more than 162044 students have viewed full stepbystep solutions from this chapter. Chapter 15.7: KRUSKALWALLIS TEST includes 10 full stepbystep solutions. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4.

Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chisquare with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chisquare random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chisquare random variables.

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Bivariate normal distribution
The joint distribution of two normal random variables

C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defectsperunit or U chart.

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

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

Conditional mean
The mean of the conditional probability distribution of a random variable.

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

Continuous distribution
A probability distribution for a continuous random variable.

Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

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.

Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

Density function
Another name for a probability density function

Distribution function
Another name for a cumulative distribution function.

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

Error of estimation
The difference between an estimated value and the true value.

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.