 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 7665 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.

Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

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

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

Causeandeffect diagram
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

Conditional mean
The mean of the conditional probability distribution of a random variable.

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

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

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.

Correlation
In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

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).

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 .

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

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

F distribution.
The distribution of the random variable deined as the ratio of two independent chisquare random variables, each divided by its number of degrees of freedom.

Ftest
Any test of signiicance involving the F distribution. The most common Ftests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.

Factorial experiment
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

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.