 Chapter 15.15.1: Anemia. Hemoglobin is a protein in red blood cells that carries oxy...
 Chapter 15.15.2: Student attitudes. The Survey of Study Habits and Attitudes (SSHA) ...
 Chapter 15.15.3: Anemia. State the null and alternative hypotheses for the anemia st...
 Chapter 15.15.4: State the null and alternative hypotheses for the study ofolder stu...
 Chapter 15.15.5: Fuel economy. According to the Environmental Protection Agency (EPA...
 Chapter 15.15.6: Travel times to work. A labor specialist thinks that the mean trave...
 Chapter 15.15.7: Stating hypotheses. In planning a study of the birth weights of bab...
 Chapter 15.15.8: Sweetening colas. Figure 15.1 compares two possible results for the...
 Chapter 15.15.9: Anemia. What are the values of the test statistic z for the two out...
 Chapter 15.15.10: Student attitudes. What are the values of the test statistic z for ...
 Chapter 15.15.11: Pvalue automated. Go to the PValue of a Test of Significance appl...
 Chapter 15.15.12: Sweetening colas. Figure 15.1 shows that the outcome x = 0.3 from t...
 Chapter 15.15.13: Anemia. What are the Pvalues for the two outcomes of the anemia st...
 Chapter 15.15.14: Student attitudes. What are the Pvalues for the two outcomes of th...
 Chapter 15.15.15: Anemia. In Exercises 15.9 and 15.13, you found the z test statistic...
 Chapter 15.15.16: Student attitudes. In Exercises 15.10 and 15.14, you found the z te...
 Chapter 15.15.17: Protecting ultramarathon runners. Exercise 9.37 (page 232) describe...
 Chapter 15.15.18: Water quality. An environmentalist group collects a liter of water ...
 Chapter 15.15.19: Improving your SAT score. We suspect that on the average students w...
 Chapter 15.15.20: Reading a computer screen. Does the use of fancy type fonts slow do...
 Chapter 15.15.21: Significance. You are testing H0: = 0 against Ha: > 0 based on an S...
 Chapter 15.15.22: Significance. You are testing H0: = 0 against Ha: = 0 based on an S...
 Chapter 15.15.23: Testing a random number generator. A random number generator is sup...
 Chapter 15.15.24: Test and confidence interval. The Pvalue for a twosided test of t...
 Chapter 15.15.25: Confidence interval and test. A 95% confidence interval for a popul...
 Chapter 15.15.26: The mean score of adult men on a psychological test that measures m...
 Chapter 15.15.27: The researchers alternative hypothesis for the test in Exercise 15....
 Chapter 15.15.28: Suppose that scores of hotel managers on the psychological test of ...
 Chapter 15.15.29: If a z statistic has value z = 1.30, the twosided Pvalue is(a) 0....
 Chapter 15.15.30: If a z statistic has value z = 1.30, the twosided Pvalue is(a) 0....
 Chapter 15.15.31: If a z statistic has value z = 1.30 and Ha says that the population...
 Chapter 15.15.32: If a z statistic has value z = 1.30 and Ha says that the population...
 Chapter 15.15.33: If a z statistic has value z = 9.03, the twosided Pvalue is(a) ve...
 Chapter 15.15.34: You use software to do a test. The program tells you that the Pval...
 Chapter 15.15.35: A government report says that a 90% confidence interval for the mea...
 Chapter 15.15.36: Sulfur compounds cause offodors in wine, so winemakers want to kno...
 Chapter 15.15.37: IQ test scores. Exercise 14.6 (page 352) gives the IQ test scores o...
 Chapter 15.15.38: Hotel managers personalities. Successful hotel managers must have p...
 Chapter 15.15.39: Bone loss by nursing mothers. Exercise 14.25 (page 358) gives the p...
 Chapter 15.15.40: Sample size affects the Pvalue. In Example 15.6, a sample of n = 1...
 Chapter 15.15.41: Tests and confidence intervals. In Exercise 14.22 you found a confi...
 Chapter 15.15.42: The Supreme Court speaks. Court cases in such areas as employmentdi...
 Chapter 15.15.43: The wrong alternative. One of your friends is comparing movie ratin...
 Chapter 15.15.44: The wrong P. The report of a study of seat belt use by drivers says...
 Chapter 15.15.45: Tracking the placebo effect. The placebo effect is particularly str...
 Chapter 15.15.46: Fortified breakfast cereals. The Food and Drug Administration recom...
 Chapter 15.15.47: How to show that you are rich. Every society has its own marks of w...
 Chapter 15.15.48: Cicadas as fertilizer? Every 17 years, swarms of cicadas emerge fro...
 Chapter 15.15.49: Forests and windstorms. Does the destruction of large trees in a wi...
 Chapter 15.15.50: Diet and bowel cancer. It has long been thought that eating a healt...
 Chapter 15.15.51: 5% versus 1%. Sketch the standard Normal curve for the z test stati...
 Chapter 15.15.52: Is this what P means? When asked to explain the meaning of the Pva...
 Chapter 15.15.53: Is this what significance means? Another student, when asked why st...
 Chapter 15.15.54: 15.54 Pulling wood apart. In Exercise 14.26 (page 359), you found a...
 Chapter 15.15.55: Im a great freethrow shooter. The Reasoning of a Statistical Test ...
 Chapter 15.15.56: Significance at the 0.0125 level. The Normal Curve applet allows yo...
Solutions for Chapter Chapter 15: Tests of Significance: The Basics
Full solutions for The Basic Practice of Statistics  4th Edition
ISBN: 9780716774785
Solutions for Chapter Chapter 15: Tests of Significance: The Basics
Get Full SolutionsThe Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785. Chapter Chapter 15: Tests of Significance: The Basics includes 56 full stepbystep solutions. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4. Since 56 problems in chapter Chapter 15: Tests of Significance: The Basics have been answered, more than 11152 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions.

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).

Average
See Arithmetic mean.

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Biased estimator
Unbiased estimator.

Chance cause
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

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.

Correlation matrix
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the offdiagonal elements rij are the correlations between Xi and Xj .

Critical value(s)
The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

Defectsperunit control chart
See U chart

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.

Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

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

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).

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.

Error of estimation
The difference between an estimated value and the true value.

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

Experiment
A series of tests in which changes are made to the system under study

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

Fraction defective control chart
See P chart