 10.10.1: Hypotheses State an appropriate pair of hypotheses for testing the ...
 10.10.2: Expected counts Joeys bag contained 46 peanut M&Ms. Calculate the e...
 10.10.3: Test statistic Calculate the chisquare statistic for Joeys sample....
 10.10.4: Pvalue Which chisquare distribution should we use? (Specify the d...
 10.10.5: Conclusion What conclusion do you draw based on the results of this...
 10.10.6: Activity 10.1 followup Use your M&Ms data from Activity 10.1 (page...
 10.10.7: Mendel and the peas Gregor Mendel (18221884), an Austrian monk, is ...
 10.10.8: Seagulls by the seashore Do seagulls show a preference for where th...
 10.10.9: Skittles Statistics teacher Jason Molesky contacted the M&M/Mars Co...
 10.10.10: More Skittles Refer to the previous exercise. (a) Create a set of o...
 10.10.11: Is your random number generator working? Use your calculators randI...
 10.10.12: Prob Sim Th e Prob Sim APP for the TI84 allows you to simulate tos...
 10.10.13: Extracurricular activities and grades, I North Carolina State Unive...
 10.10.14: Extracurricular activities and grades, II Refer to Exercise 10.13. ...
 10.10.15: Trying to quit, I An observational study of 177 people who were try...
 10.10.16: Trying to quit, II Refer to Exercise 10.15. (a) Write the null and ...
 10.10.17: Python eggs, I How is the hatching of water python eggs infl uenced...
 10.10.18: Python eggs, II Refer to Exercise 10.17. (a) Write the null and alt...
 10.10.19: Extracurricular activities and grades, III In Exercises 10.13 and 1...
 10.10.20: Trying to quit, III In Exercise 10.15 (page 484), you saw an appare...
 10.10.21: Python eggs, III Exercise 10.17 (page 485) presented data on the ha...
 10.10.22: Smoking by students and their parents How are the smoking habits of...
 10.10.23: Cocaine addiction is hard to break, I Cocaine addicts need the drug...
 10.10.24: Cocaine addiction is hard to break, II Refer to the previous exerci...
 10.10.25: Finding Pvalues Use Table E (in the back of the book) to fi nd the...
 10.10.26: Munching Froot Loops Kelloggs Froot Loops cereal comes in six fruit...
 10.10.27: Majors for men and women in business, I A study of the career plans...
 10.10.28: Majors for men and women in business, II Exercise 10.27 gives the r...
 10.10.29: Birds in the trees Researchers studied the behavior of birds that w...
 10.10.30: Preventing domestic violence A study conducted in Charlotte, North ...
 10.10.31: Is this coin fair? A statistics student suspected that his penny wa...
 10.10.32: Totals arent enough Here are the row and column totals for a twowa...
 10.10.33: Th e idea of a sampling distribution Figure 9.2 (page 423) shows th...
 10.10.34: Averages versus individuals Scores on the American College Testing ...
 10.10.35: A sampling distribution, I We used our calculators rand function to...
 10.10.36: A sampling distribution, II Exercise 10.35 presents 50 sample means...
 10.10.37: Student attitudes Th e Survey of Study Habits and Attitudes (SSHA) ...
 10.10.38: Th e CLT applet Go to the textbook Web site, www.whfreeman.com/sta2...
 10.10.39: Confi dence level and margin of error Th e NAEP test (Example 10.11...
 10.10.40: Executives blood pressure Example 10.12 (page 500) found that the m...
 10.10.41: Charge more, I Is there signifi cant evidence at the 1% level that ...
 10.10.42: Charge more, II Calculate and interpret a 99% confi dence interval ...
 10.10.43: Charge more, III In Exercises 10.41 and 10.42, you carried out the ...
 10.10.44: Normal body temperature In Application 1.2 (page 25), we described ...
 10.10.45: Finding critical values What critical value t* from Table C should ...
 10.10.46: Blood pressure A randomized comparative experiment studied the eff ...
 10.10.47: Caff eine and depression Refer to Example 10.15 (page 507). Th e re...
 10.10.48: Healthy streams Refer to Example 10.14 (page 506). Do the data prov...
 10.10.49: Sleepless nights An experiment was carried out with 10 patients to ...
 10.10.50: Darwins plants Charles Darwin, author of Th e Origin of Species (18...
 10.10.51: Explaining confi dence A student reads that a 95% confi dence inter...
 10.10.52: Whats the average height? One hundred and fi ft y students attend t...
 10.10.53: Airline passengers get heavier In response to the increasing weight...
 10.10.54: One tail or two? What null and alternative hypotheses should you te...
 10.10.55: Pleasant smells, I Do pleasant odors help work go faster? Twentyon...
 10.10.56: Pleasant smells, II Return to the data in Exercise 10.55. Calculate...
 10.10.57: Study more! A student group claims that fi rstyear students at a u...
 10.10.58: IQ at BCU Th e admissions director at Big City University has a new...
 10.10.59: Longerlasting batteries A company that produces AA batteries makes...
 10.10.60: Representative sample? For a class project, a statistics student is...
 10.10.61: Call the paramedics! Vehicle accidents can result in serious injuri...
 10.10.62: Tall girls Based on information from the National Center for Health...
 10.10.63: Popular kids, I Who were the popular kids at your elementary school...
 10.10.64: Popular kids, II Refer to the previous exercise. Is there convincin...
 10.10.65: Good news for chocolate lovers? A German study concluded that dark ...
 10.10.66: Sleepy students? A sample of 28 college students responded to the s...
 10.10.67: Acupuncture and pregnancy A study was performed to determine if the...
 10.10.68: Mercury in tuna As we discussed in Chapter 2 (page 56), some of the...
Solutions for Chapter 10: Inference in Practice
Full solutions for Statistics Through Applications  2nd Edition
ISBN: 9781429219747
Solutions for Chapter 10: Inference in Practice
Get Full SolutionsSince 68 problems in chapter 10: Inference in Practice have been answered, more than 14556 students have viewed full stepbystep solutions from this chapter. Statistics Through Applications was written by and is associated to the ISBN: 9781429219747. Chapter 10: Inference in Practice includes 68 full stepbystep solutions. This textbook survival guide was created for the textbook: Statistics Through Applications, edition: 2. This expansive textbook survival guide covers the following chapters and their solutions.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

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

Addition rule
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

Average
See Arithmetic mean.

Average run length, or ARL
The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

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.

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.

Crossed factors
Another name for factors that are arranged in a factorial experiment.

Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

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

Defectsperunit control chart
See U chart

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

Error variance
The variance of an error term or component in a model.

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

Expected value
The expected value of a random variable X is its longterm average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

False alarm
A signal from a control chart when no assignable causes are present

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

Generator
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.