×
×

# 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

Solutions for Chapter 15.7
4 5 0 344 Reviews
25
4
##### ISBN: 9780321757272

Since 10 problems in chapter 15.7: KRUSKALWALLIS TEST have been answered, more than 162044 students have viewed full step-by-step solutions from this chapter. Chapter 15.7: KRUSKALWALLIS TEST includes 10 full step-by-step 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.

Key Statistics Terms and definitions covered in this textbook
• Additivity property of x 2

If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square 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 defects-per-unit or U chart.

• Chi-square test

Any test of signiicance based on the chi-square distribution. The most common chi-square 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 Moment-generating 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.

×