 8.8.1: Smartphones and purchases. A Google research study asked 5013 smart...
 8.8.2: Past usage of Facebook. Refer to the Pew Internet survey described ...
 8.8.3: Smartphones and purchases. Refer to Exercise 8.1 (page 489). (a) Fi...
 8.8.4: Past usage of Facebook. Refer to Exercise 8.2 (page 489). (a) Find ...
 8.8.5: Draw a picture. Draw a picture of a standard Normal curve and shade...
 8.8.6: What does the confidence interval tell us? Inspect the outputs in F...
 8.8.7: The effect of X. In Example 8.5, suppose that your product provided...
 8.8.8: The effect of n. In Example 8.5, consider what would have happened ...
 8.8.9: Redefining success. In Example 8.5 we performed a significance test...
 8.8.10: Confidence level and sample size. Refer to Example 8.7 (page 501). ...
 8.8.11: Make a plot. Use the values for p and m given in Example 8.9 to dra...
 8.8.12: How did you use your cell phone? A Pew Internet poll asked cell pho...
 8.8.13: Do you eat breakfast? A random sample of 200 students from your col...
 8.8.14: Would you recommend the service to a friend? An automobile dealersh...
 8.8.15: How did you use your cell phone? Refer to Exercise 8.12. (a) Report...
 8.8.16: Do you eat breakfast? Refer to Exercise 8.13. (a) Report the sample...
 8.8.17: Would you recommend the service to a friend? Refer to Exercise 8.14.
 8.8.18: Whole grain versus regular grain? A study of young children was des...
 8.8.19: Find the sample size. You are planning a survey similar to the one ...
 8.8.20: Whats wrong? Explain what is wrong with each of the following: (a) ...
 8.8.21: Whats wrong? Explain what is wrong with each of the following: (a) ...
 8.8.22: Draw some pictures. Consider the binomial setting with n100 and p0....
 8.8.23: Country food and Inuits. Country food includes seals, caribou, whal...
 8.8.24: Soft drink consumption in New Zealand. A survey commissioned by the...
 8.8.25: Violent video games. A 2013 survey of 1050 parents who have a child...
 8.8.26: Bullying. Refer to the previous exercise. The survey also reported ...
 8.8.27: p and the Normal distribution. Consider the binomial setting with n...
 8.8.28: Students doing community service. In a sample of 159,949 firstyear...
 8.8.29: Plans to study abroad. The survey described in the previous exercis...
 8.8.30: Student credit cards. In a survey of 1430 undergraduate students, 1...
 8.8.31: How many credit cards? The summary of the survey described in the p...
 8.8.32: How would the confidence interval change? Refer to Exercise 8.31. (...
 8.8.33: Do students report Internet sources? The National Survey of Student...
 8.8.34: Can we use the z test? In each of the following cases state whether...
 8.8.35: sample of sermons at their congregations. They responded based on t...
 8.8.36: Confidence level and interval width. Refer to the previous exercise...
 8.8.37: Instant versus freshbrewed coffee. A matched pairs experiment comp...
 8.8.38: Annual income of older adults. In a study of older adults, 1444 sub...
 8.8.39: Tossing a coin 10,000 times! The South African mathematician John K...
 8.8.40: Is there interest in a new product? One of your employees has sugge...
 8.8.41: More information is needed. Refer to the previous exercise. Suppose...
 8.8.42: Sample size needed for an evaluation. You are planning an evaluatio...
 8.8.43: Sample size needed for an evaluation, continued. The evaluation in ...
 8.8.44: Are the customers dissatisfied? An automobile manufacturer would li...
 8.8.45: Rules for means and variances. Suppose that p1 0.3, n1 20, p2 0.6, ...
 8.8.46: Effect of the sample sizes. Suppose that p1 0.3, n1 80, p2 0.6, n2 ...
 8.8.47: Rules for means and variances. It is quite easy to verify the formu...
 8.8.48: Gender and commercial preference. A study was designed to compare t...
 8.8.49: Gender and commercial preference, revisited. Refer to Exercise 8.48...
 8.8.50: Gender and commercial preference: the z test. Refer to Exercise 8.4...
 8.8.51: Changing the alternative hypothesis. Refer to the previous exercise...
 8.8.52: Identify the key elements. For each of the following scenarios, ide...
 8.8.53: Apply the confidence interval guidelines. Refer to the previous exe...
 8.8.54: Find the 95% confidence interval. Refer to Exercise 8.52. For each ...
 8.8.55: Apply the significance test guidelines.
 8.8.56: Perform the significance test. Refer to Exercise 8.52. For each sce...
 8.8.57: Find the relative risk. Refer to Exercise 8.52. For each scenario, ...
 8.8.58: Teeth and military service. In 1898 the United States and Spain fou...
 8.8.59: Physical education requirements. In the 1920s, about 97% of U.S. co...
 8.8.60: Exergaming in Canada. Exergames are active video games such as rhyt...
 8.8.61: Confidence interval for exergaming in Canada. Refer to the previous...
 8.8.62: Significance test for exergaming in Canada. Refer to Exercise 8.60....
 8.8.63: Adult gamers versus teen gamers. A Pew Internet Project Data Memo p...
 8.8.64: Significance test for gaming on consoles. Refer to the previous exe...
 8.8.65: Gamers on computers. The report described in Exercise 8.63 also pre...
 8.8.66: Significance test for gaming on computers. Refer to the previous ex...
 8.8.67: Can we compare gaming on consoles with gaming on computers? Refer t...
 8.8.68: Draw a picture. Suppose that there are two binomial populations. Fo...
 8.8.69: Whats wrong? For each of the following, explain what is wrong and w...
 8.8.70: p 1 2 p 2 and the Normal distribution. Refer to Exercise 8.68. Assu...
 8.8.71: Gender bias in textbooks. To what extent do syntax textbooks, which...
 8.8.72: The future of gamification. Gamification is an interactive design t...
 8.8.73: Where do you get your news? A report produced by the Pew Research C...
 8.8.74: Is the calcium intake adequate? Young children need calcium in thei...
 8.8.75: Use a confidence interval for the comparison. Refer to the previous...
 8.8.76: Use a significance test for the comparison. Refer to Exercise 8.74....
 8.8.77: Confidence interval or significance test? Refer to Exercises 8.74 t...
 8.8.78: Punxsutawney Phil. There is a gathering every year on February 2 at...
 8.8.79: Facebook users. A Pew survey of 1802 Internet users found that 67% ...
 8.8.80: Twitter users. Refer to the previous exercise. The same survey repo...
 8.8.81: Facebook versus Twitter. Refer to Exercises 8.79 and 8.80. Can you ...
 8.8.82: Video game genres. U.S. computer and video game software sales were...
 8.8.83: Too many errors. Refer to the previous exercise. The chance that ea...
 8.8.84: Changes in credit card usage by undergraduates. In Exercise 8.31 (p...
 8.8.85: Do the significance test for the change. Refer to the previous exer...
 8.8.86: We did not know the sample size. Refer to the previous two exercise...
 8.8.87: Student employment during the school year. A study of 1530 undergra...
 8.8.88: Examine the effect of the sample size. Refer to the previous exerci...
 8.8.89: Gender and soft drink consumption. Refer to Exercise 8.24 (page 505...
 8.8.90: Examine the effect of the sample size. Refer to the previous exerci...
 8.8.91: Gallup Poll study. Go to the Gallup Poll website gallup.com and fin...
 8.8.92: More on gender bias in textbooks. Refer to the study of gender bias...
 8.8.93: Even more on gender bias in textbooks. Refer to the previous exerci...
 8.8.94: Changing majors during college. In a random sample of 975 students ...
 8.8.95: Sample size and the Pvalue. In this exercise we examine the effect...
 8.8.96: Sample size and the margin of error. In Section 8.1, we studied the...
 8.8.97: Calculating sample sizes for the twosample problem. For a single p...
 8.8.98: A corporate liability trial. A major court case on the health effec...
 8.8.99: Statistics and the law. Castaneda v. Partida is an important court ...
 8.8.100: Home court advantage. In many sports there is a home field or home ...
 8.8.101: Attitudes toward student loan debt. The National Student Loan Surve...
Solutions for Chapter 8: Inference for Proportions
Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card  8th Edition
ISBN: 9781464158933
Solutions for Chapter 8: Inference for Proportions
Get Full SolutionsSince 101 problems in chapter 8: Inference for Proportions have been answered, more than 31571 students have viewed full stepbystep solutions from this chapter. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933. Chapter 8: Inference for Proportions includes 101 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8.

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

Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

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.

Bias
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

Box plot (or box and whisker plot)
A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

Central composite design (CCD)
A secondorder response surface design in k variables consisting of a twolevel factorial, 2k axial runs, and one or more center points. The twolevel 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 secondorder model.

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

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

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

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 .

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

Design matrix
A matrix that provides the tests that are to be conducted in an experiment.

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

Distribution free method(s)
Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

Empirical model
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

Fisher’s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Gaussian distribution
Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .