 Chapter 21.21.1: Who uses instant messaging? Teenagers (ages 12 to 17) are much more...
 Chapter 21.21.2: How to quit smoking. Nicotine patches are often used to help smoker...
 Chapter 21.21.3: Broken crackers. We dont like to find broken crackers when we open ...
 Chapter 21.21.4: Inline skaters. A study of injuries to inline skaters used data f...
 Chapter 21.21.5: The Gold Coast.Coast in Africa suspects that the death rate was hig...
 Chapter 21.21.6: How to quit smoking, continued. Exercise 21.2 describes a randomize...
 Chapter 21.21.7: Take pM and p F to be the proportions of all college males and fema...
 Chapter 21.21.8: The sample proportions of college males and females who worked last...
 Chapter 21.21.9: The pooled sample proportion who worked last summer is about(a) p =...
 Chapter 21.21.10: The z statistic for a test comparing the proportions of college men...
 Chapter 21.21.11: The 95% largesample confidence interval for the difference pM p F ...
 Chapter 21.21.12: In an experiment to learn if substance M can help restore memory, t...
 Chapter 21.21.13: The z test in the previous exercise(a) may be inaccurate because th...
 Chapter 21.21.14: The plus four 90% confidence interval for the difference between th...
 Chapter 21.21.15: Genetically altered mice. Genetic influences on cancer can be studi...
 Chapter 21.21.16: Drug testing in schools. In 2002 the Supreme Court ruled that schoo...
 Chapter 21.21.17: I Do our emotions influence economic decisions? One way to examine ...
 Chapter 21.21.18: Exercise 21.16 describes a study thatcompared the proportions of at...
 Chapter 21.21.19: Does statistical help make a difference? Is there a significant dif...
 Chapter 21.21.20: How often are statisticians involved? Give a 95% confidence interva...
 Chapter 21.21.21: How big a difference? Give a 95% confidence interval for the differ...
 Chapter 21.21.22: A study by the National Athletic Trainers Associationsurveyed 1679 ...
 Chapter 21.21.23: Exercise 20.35 (page 509) describesa study in which batches of soyb...
 Chapter 21.21.24: Never forget that even small effects canbe statistically significan...
 Chapter 21.21.25: A sample survey asked 202 black parents and201 white parents of hig...
 Chapter 21.21.26: The sample survey described in the previous exercise alsoasked resp...
 Chapter 21.21.27: The proportion of drivers who use seat belts depends on thingslike ...
 Chapter 21.21.28: Here are data from the study described in theprevious exercise for ...
 Chapter 21.21.29: Lyme disease is spread in the northeastern United States byinfected...
 Chapter 21.21.30: Are urban students more successful? North Carolina State University...
 Chapter 21.21.31: Does preschool help? To study the longterm effects of preschool pr...
 Chapter 21.21.32: The North Carolina State University study(Exercise 21.30) also look...
 Chapter 21.21.33: The study in Exercise 21.31 randomly assigned 123 children tothe tw...
 Chapter 21.21.34: Are shoppers more or less likely to use credit cards forimpulse pur...
Solutions for Chapter Chapter 21: Comparing Two Proportions
Full solutions for The Basic Practice of Statistics  4th Edition
ISBN: 9780716774785
Solutions for Chapter Chapter 21: Comparing Two Proportions
Get Full SolutionsChapter Chapter 21: Comparing Two Proportions includes 34 full stepbystep solutions. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4. Since 34 problems in chapter Chapter 21: Comparing Two Proportions have been answered, more than 7732 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785.

Bayes’ estimator
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

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

C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defectsperunit or U chart.

Chisquare (or chisquared) 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.

Confounding
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Control limits
See Control chart.

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.

Covariance
A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

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

Density function
Another name for a probability density function

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

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

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

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.

Fraction defective control chart
See P chart

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

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 .