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# Solutions for Chapter 8-1: Steps in Hypothesis TestingTraditional Method

## Full solutions for Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition

ISBN: 9780073386102

Solutions for Chapter 8-1: Steps in Hypothesis TestingTraditional Method

Solutions for Chapter 8-1
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##### ISBN: 9780073386102

Chapter 8-1: Steps in Hypothesis TestingTraditional Method includes 13 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. This expansive textbook survival guide covers the following chapters and their solutions. Since 13 problems in chapter 8-1: Steps in Hypothesis TestingTraditional Method have been answered, more than 36830 students have viewed full step-by-step solutions from this chapter. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102.

Key Statistics Terms and definitions covered in this textbook
• Attribute control chart

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

• Bimodal distribution.

A distribution with two modes

• Chance cause

The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

• Chi-square (or chi-squared) 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.

• Completely randomized design (or experiment)

A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

• Control limits

See Control chart.

• Correction factor

A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

• Correlation

In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

• Curvilinear regression

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

• Dependent variable

The response variable in regression or a designed experiment.

• Distribution free method(s)

Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

• Distribution function

Another name for a cumulative distribution function.

• Error mean square

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

• Exponential random variable

A series of tests in which changes are made to the system under study

• Fisher’s least signiicant difference (LSD) method

A series of pair-wise 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

• 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

• Harmonic mean

The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .

• 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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