 9.2.31: In Exercises 31 and 32, check that the conditions for carrying out ...
 9.2.32: In Exercises 31 and 32, check that the conditions for carrying out ...
 9.2.33: In Exercises 33 and 34, explain why we arent safe carrying out a on...
 9.2.34: In Exercises 33 and 34, explain why we arent safe carrying out a on...
 9.2.35: Home computers Refer to Exercise 31. In Jasons SRS, 41 of the stude...
 9.2.36: Walking to school Refer to Exercise 32. For DeAnnas survey, 17 stud...
 9.2.37: Significance tests A test of H0 :p = 0.5 versus Ha :p > 0.5 has tes...
 9.2.38: Significance tests A test of H0 :p = 0.65 against Ha :p < 0.65 has ...
 9.2.39: Better parking A local high school makes a change that should impro...
 9.2.40: Side effects A drug manufacturer claims that less than 10% of patie...
 9.2.41: Are boys more likely? We hear that newborn babies are more likely t...
 9.2.42: Fresh coffee People of taste are supposed to prefer freshbrewed co...
 9.2.43: Bullies in middle school A University of Illinois study on aggressi...
 9.2.44: Is this coin fair? The French naturalist Count Buffon (17071788) to...
 9.2.45: Teen drivers A states Division of Motor Vehicles (DMV) claims that ...
 9.2.46: We want to be rich In a recent year, 73% of firstyear college stude...
 9.2.47: Teen drivers Refer to Exercise 45. (a) Construct and interpret a 95...
 9.2.48: We want to be rich Refer to Exercise 46. (a) Construct and interpre...
 9.2.49: Do you Tweet? In early 2012, the Pew Internet and American Life Pro...
 9.2.50: Losing weight A Gallup Poll found that 59% of the people in its sam...
 9.2.51: Teens and sex The Gallup Youth Survey asked a random sample of U.S....
 9.2.52: Reporting cheating What proportion of students are willing to repor...
 9.2.53: Better parking Refer to Exercise 39. (a) Describe a Type I error an...
 9.2.54: Side effects Refer to Exercise 40. (a) Describe a Type I error and ...
 9.2.55: Error probabilities You read that a statistical test at significanc...
 9.2.56: Error probabilities You read that a statistical test at the a = 0.0...
 9.2.57: Power A drug manufacturer claims that fewer than 10% of patients wh...
 9.2.58: What is power? You manufacture and sell a liquid product whose elec...
 9.2.59: Multiple choice: Select the best answer for Exercises 59 to 62. Aft...
 9.2.60: Multiple choice: Select the best answer for Exercises 59 to 62. Whi...
 9.2.61: Multiple choice: Select the best answer for Exercises 59 to 62. The...
 9.2.62: Multiple choice: Select the best answer for Exercises 59 to 62. Whi...
 9.2.63: Packaging CDs (6.2, 5.3) A manufacturer of compact discs (CDs) want...
 9.2.64: Cash to find work? (4.2) Will cash bonuses speed the return to work...
Solutions for Chapter 9.2: Tests about a Population Proportion
Full solutions for The Practice of Statistics  5th Edition
ISBN: 9781464108730
Solutions for Chapter 9.2: Tests about a Population Proportion
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730. Since 34 problems in chapter 9.2: Tests about a Population Proportion have been answered, more than 9072 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. Chapter 9.2: Tests about a Population Proportion includes 34 full stepbystep solutions.

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

Conditional variance.
The variance of the conditional probability distribution of a random variable.

Conidence level
Another term for the conidence coeficient.

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 incontrol 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 incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

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.

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

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.

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

Discrete random variable
A random variable with a inite (or countably ininite) range.

Estimate (or point estimate)
The numerical value of a point estimator.

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.

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 .
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