 Chapter 4 .4.1: Explanatory and response variables? You have data on a large group ...
 Chapter 4 .4.2: Coral reefs. How sensitive to changes in water temperature are cora...
 Chapter 4 .4.3: Beer and blood alcohol. Example 4.1 describes a study in which coll...
 Chapter 4 .4.4: Bird colonies. One of natures patterns connects the percent of adul...
 Chapter 4 .4.5: Bird colonies. Describe the form, direction, and strength of the re...
 Chapter 4 .4.6: Does fast driving waste fuel? How does the fuel consumption of a ca...
 Chapter 4 .4.7: How fast do icicles grow? Japanese researchers measured the growth ...
 Chapter 4 .4.8: Coffee and deforestation. Coffee is a leading export from several d...
 Chapter 4 .4.9: Changing the units. Coffee is currently priced in dollars. If it we...
 Chapter 4 .4.11: Strong association but no correlation. The gas mileage of an automo...
 Chapter 4 .4.12: You have data for many families on the parents income and the years...
 Chapter 4 .4.13: You have data for many families on the parents income and the years...
 Chapter 4 .4.14: Figure 4.6 is a scatterplot of reading test scores against IQ test ...
 Chapter 4 .4.15: Removing the outlier in Figure 4.6 would(a) increase the correlatio...
 Chapter 4 .4.16: If we leave out the low outlier, the correlation for the remaining ...
 Chapter 4 .4.17: What are all the values that a correlation r can possibly take?(a) ...
 Chapter 4 .4.18: The points on a scatterplot lie very close to the line whose equati...
 Chapter 4 .4.19: If women always married men who were 2 years older than themselves,...
 Chapter 4 .4.21: Because elderly people may have difficulty standing to have their h...
 Chapter 4 .4.22: Stocks versus Tbills. What is the relationship between returns fro...
 Chapter 4 .23: Can children estimate their own reading ability? To study this ques...
 Chapter 4 .4.24: Data on dating. A student wonders if tall women tend to date taller...
 Chapter 4 .4.25: World record running times. Table 4.3 shows the progress of world r...
 Chapter 4 .4.26: Thinking about correlation. Exercise 4.24 presents data on the heig...
 Chapter 4 .4.27: Heating a home. The Sanchez household is about to install solar pan...
 Chapter 4 .4.28: How many corn plants are too many? How much corn per acre should af...
 Chapter 4 .4.29: Do solar panels reduce gas usage? After the Sanchez household gathe...
 Chapter 4 .4.31: Statistics for investing. Investment reports now often include corr...
 Chapter 4 .4.32: Statistics for investing. A mutualfunds companys newsletter says, ...
 Chapter 4 .4.33: The effect of changing units. Changing the units of measurement can...
 Chapter 4 .4.34: Teaching and research. A college newspaper interviews a psychologis...
 Chapter 4 .4.35: Sloppy writing about correlation. Each of the following statements ...
 Chapter 4 .4.36: Correlation is not resistant. Go to the Correlation and Regression ...
 Chapter 4 .4.37: Match the correlation. You are going to use the Correlation and Reg...
 Chapter 4 .4.38: Brighter sunlight? The brightness of sunlight at the earths surface...
 Chapter 4 .4.39: Merlins breeding. Often the percent of an animal species in the wil...
 Chapter 4 .4.41: Hot mutual funds? The data for 2003 in Exercise 4.30 make sector fu...
Solutions for Chapter Chapter 4 : Scatterplots and Correlation
Full solutions for The Basic Practice of Statistics  4th Edition
ISBN: 9780716774785
Solutions for Chapter Chapter 4 : Scatterplots and Correlation
Get Full SolutionsSince 37 problems in chapter Chapter 4 : Scatterplots and Correlation have been answered, more than 7732 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter Chapter 4 : Scatterplots and Correlation includes 37 full stepbystep solutions. This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4. The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785.

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

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

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

Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

Bivariate distribution
The joint probability distribution of two random variables.

Bivariate normal distribution
The joint distribution of two normal random variables

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

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 mass function
The probability mass function of the conditional probability distribution of a discrete random variable.

Control limits
See Control chart.

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.

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 .

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

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.

Distribution function
Another name for a cumulative distribution function.

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.

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

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

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 .