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# Solutions for Chapter 1.4: Elementary Statistics 12th Edition ## Full solutions for Elementary Statistics | 12th Edition

ISBN: 9780321836960 Solutions for Chapter 1.4

Solutions for Chapter 1.4
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##### ISBN: 9780321836960

This textbook survival guide was created for the textbook: Elementary Statistics, edition: 12. This expansive textbook survival guide covers the following chapters and their solutions. Since 68 problems in chapter 1.4 have been answered, more than 213393 students have viewed full step-by-step solutions from this chapter. Chapter 1.4 includes 68 full step-by-step solutions. Elementary Statistics was written by and is associated to the ISBN: 9780321836960.

Key Statistics Terms and definitions covered in this textbook
• 2 k factorial experiment.

A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

• `-error (or `-risk)

In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

• 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.

• Binomial random variable

A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

• Causal variable

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

• Conditional mean

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

• Conditional probability mass function

The probability mass function of the conditional probability distribution of a discrete random variable.

• Conidence level

Another term for the conidence coeficient.

• Continuous random variable.

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

• Convolution

A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

• Cook’s distance

In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

• Cumulative sum control chart (CUSUM)

A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

• Dependent variable

The response variable in regression or a designed experiment.

• Error mean square

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

• Event

A subset of a sample space.

• Exhaustive

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

• F distribution.

The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.

• Gamma function

A function used in the probability density function of a gamma random variable that can be considered to extend factorials

• Generator

Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

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