 Chapter 3.3.1: Sketch density curves. Sketch density curves that describe distribu...
 Chapter 3.3.2: A uniform distribution. Figure 3.6 displays the density curve of a ...
 Chapter 3.3.3: Mean and median. What is the mean of the density curve pictured in ...
 Chapter 3.3.4: Mean and median. Figure 3.7 displays three density curves, each wit...
 Chapter 3.3.5: Heights of young women. The distribution of heights of women aged 2...
 Chapter 3.3.6: Heights of young women. The distribution of heights of women aged 2...
 Chapter 3.3.7: Length of pregnancies. The length of human pregnancies from concept...
 Chapter 3.3.8: SAT versus ACT. Eleanor scores 680 on the mathematics part of the S...
 Chapter 3.3.9: Mens and womens heights. The heights of women aged 20 to 29 areappr...
 Chapter 3.3.11: How hard do locomotives pull? An important measure of the performan...
 Chapter 3.3.12: A better locomotive. Improvements in the locomotives computer contr...
 Chapter 3.3.13: Table A. Use Table A to find the value z of a standard Normal varia...
 Chapter 3.3.14: IQ test scores. Scores on the Wechsler Adult Intelligence Scale are...
 Chapter 3.3.15: Which of these variables is least likely to have a Normal distribut...
 Chapter 3.3.16: To completely specify the shape of a Normal distribution, you must ...
 Chapter 3.3.17: Figure 3.14 shows a Normal curve. The mean of this distribution is(...
 Chapter 3.3.18: The standard deviation of the Normal distribution in Figure 3.14 is...
 Chapter 3.3.19: The length of human pregnancies from conception to birth varies acc...
 Chapter 3.3.21: The scores of adults on an IQ test are approximately Normal with me...
 Chapter 3.3.22: The proportion of observations from a standard Normal distribution ...
 Chapter 3.3.23: The proportion of observations from a standard Normal distribution ...
 Chapter 3.3.24: The scores of adults on an IQ test are approximately Normal with me...
 Chapter 3.3.25: Understanding density curves. Remember that it is areas under a den...
 Chapter 3.3.26: Are the data Normal? Soil penetrability. Table 2.3 (page 61) gives ...
 Chapter 3.3.27: IQ test scores. The Wechsler Adult Intelligence Scale (WAIS) is the...
 Chapter 3.3.28: Low IQ test scores. Scores on the Wechsler Adult Intelligence Scale...
 Chapter 3.3.29: Actual IQ test scores. Here are the IQ test scores of 31 seventhgr...
 Chapter 3.3.31: Standard Normal drill.(a) Find the number z such that the proportio...
 Chapter 3.3.32: Tonya scores 1318 on the SAT. Jermaine scores 27 on the ACT. Assumi...
 Chapter 3.3.33: Jacob scores 16 on the ACT. Emily scores 670 on the SAT. Assuming t...
 Chapter 3.3.34: Jos e scores 1287 on the SAT. Assuming that both tests measure the ...
 Chapter 3.3.35: Maria scores 28 on the ACT. Assuming that both tests measure the sa...
 Chapter 3.3.36: Reports on a students ACT or SAT usually give the percentile as wel...
 Chapter 3.3.37: Reports on a students ACT or SAT usually give the percentile as wel...
 Chapter 3.3.38: It is possible to score higher than 1600 on the SAT, but scores 160...
 Chapter 3.3.39: It is possible to score higher than 36 on the ACT, but scores 36 an...
 Chapter 3.3.41: How well must Abigail do on the ACT in order to place in the top 20...
 Chapter 3.3.42: The quartiles of any distribution are the values with cumulative pr...
 Chapter 3.3.43: The quintiles of any distribution are the values with cumulative pr...
 Chapter 3.3.44: Heights of men and women. The heights of women aged 20 to 29 follow...
 Chapter 3.3.45: Heights of men and women. The heights of women aged 20 to 29 follow...
 Chapter 3.3.46: A surprising calculation. Changing the mean of a Normal distributio...
 Chapter 3.3.47: Grading managers. Many companies grade on a bell curve to compare t...
 Chapter 3.3.48: Osteoporosis. Osteoporosis is a condition in which the bones become...
 Chapter 3.3.49: Are the data Normal? ACT scores. Scores on the ACT test for the 200...
 Chapter 3.3.51: How accurate is 689599.7? The 689599.7 rule for Normal distribution...
 Chapter 3.3.52: Where are the quartiles? How many standard deviations above and bel...
 Chapter 3.3.53: Grading managers. In Exercise 3.47, we saw that Ford Motor Company ...
Solutions for Chapter Chapter 3: The Normal Distributions
Full solutions for The Basic Practice of Statistics  4th Edition
ISBN: 9780716774785
Solutions for Chapter Chapter 3: The Normal Distributions
Get Full SolutionsChapter Chapter 3: The Normal Distributions includes 48 full stepbystep solutions. The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785. Since 48 problems in chapter Chapter 3: The Normal Distributions have been answered, more than 13672 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4.

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

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

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.

Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

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.

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

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.

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

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

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.

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

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

Event
A subset of a sample space.

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

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

Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

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

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.

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .