- 8.R8.1: Conditions Martin says that the relative importance of the three co...
- 8.R8.2: Its critical Find the appropriate critical value for constructing a...
- 8.R8.3: Batteries A company that produces AA batteries tests the lifetime o...
- 8.R8.4: We love football! A recent Gallup Poll conducted telephone intervie...
- 8.R8.5: Smart kids A school counselor wants to know how smart the students ...
- 8.R8.6: Do you go to church? The Gallup Poll plans to ask a random sample o...
- 8.R8.7: Running red lights A random digit dialing telephone survey of 880 d...
- 8.R8.8: Engine parts Here are measurements (in millimeters) of a critical d...
- 8.R8.9: Good wood? A lab supply company sells pieces of Douglas fir 4 inche...
Solutions for Chapter 8: The Practice of Statistics 4th Edition
Full solutions for The Practice of Statistics | 4th Edition
All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions
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.
Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.
Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
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.
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.
The mean of the conditional probability distribution of a random variable.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made
A probability distribution for a continuous random variable.
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.
The amount of variability exhibited by data
Another name for a cumulative distribution function.
Extra sum of squares method
A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.
A signal from a control chart when no assignable causes are present
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function
Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.
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