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# Solutions for Chapter 7-2: Confidence Intervals for the Mean When s Is Unknown

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

ISBN: 9780073386102

Solutions for Chapter 7-2: Confidence Intervals for the Mean When s Is Unknown

Solutions for Chapter 7-2
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##### ISBN: 9780073386102

This expansive textbook survival guide covers the following chapters and their solutions. Since 21 problems in chapter 7-2: Confidence Intervals for the Mean When s Is Unknown have been answered, more than 34455 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. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Chapter 7-2: Confidence Intervals for the Mean When s Is Unknown includes 21 full step-by-step solutions.

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.

• a-error (or a-risk)

In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

• Analytic study

A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

• 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.

• Central composite design (CCD)

A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.

• Continuity correction.

A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

• Control chart

A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

• Defect concentration diagram

A quality tool that graphically shows the location of defects on a part or in a process.

• Defects-per-unit control chart

See U chart

• Deining relation

A subset of effects in a fractional factorial design that deine the aliases in the design.

• Deming

W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

• Discrete uniform random variable

A discrete random variable with a inite range and constant probability mass function.

• Eficiency

A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

• Estimator (or point estimator)

A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

• 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.

• Finite population correction factor

A term in the formula for the variance of a hypergeometric random variable.

• Fixed factor (or fixed effect).

In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

• Fraction defective control chart

See P chart

• Geometric mean.

The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .

• 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 .

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