 2.2.1: The categories by which data are grouped are called .
 2.2.1E: The categories by which data are grouped are called __________
 2.2.2: The class limit is the smallest value within the class and the clas...
 2.2.2E: The _______ class limit is the smallest value within the class and ...
 2.2.3: The is the difference between consecutive lower class limits.
 2.2.3E: The ____ ____ is the difference between consecutive lower class lim...
 2.2.4: What does it mean if a distribution is said to be skewed left?
 2.2.4E: What does it mean if a distribution is said to be “skewed left”?
 2.2.5: True or False: There is not one particular frequency distribution t...
 2.2.5E: True or False: There is not one particular frequency distribution t...
 2.2.6: True or False: Stemandleaf plots are particularly useful for larg...
 2.2.6E: True or False: Stemandleaf plots are particularly useful for larg...
 2.2.7: True or False: The shape of the distribution shown is best classifi...
 2.2.7E: True or False: The shape of the distribution shown is best classifi...
 2.2.8: True or False: The shape of the distribution shown is best classifi...
 2.2.8E: True or False: The shape of the distribution shown is best classifi...
 2.2.9: Rolling the Dice An experiment was conducted in which two fair dice...
 2.2.9E: Rolling the Dice An experiment was conducted in which two fair dice...
 2.2.10E: Car Sales A car salesman records the number of cars he sold each we...
 2.2.10: IQ Scores The following frequency histogram represents the IQ score...
 2.2.11E: IQ Scores The following frequency histogram represents the IQ score...
 2.2.11: AlcoholRelated Traffic Fatalities The frequency histogram in the n...
 2.2.12E: AlcoholRelated Traffic Fatalities The frequency histogram in the n...
 2.2.12: AlcoholRelated Traffic Fatalities The frequency histogram in the n...
 2.2.13E: In Problem, for each variable presented, state whether you would ex...
 2.2.13: In 13 and 14, for each variable presented, state whether you would ...
 2.2.14E: In Problem, for each variable presented, state whether you would ex...
 2.2.14: In 13 and 14, for each variable presented, state whether you would ...
 2.2.15E: Predicting School Enrollment To predict future enrollment, a local ...
 2.2.15: Predicting School Enrollment To predict future enrollment, a local ...
 2.2.16E: Free Throws A basketball player habitually makes 70% of her free th...
 2.2.16: (a) Construct a relative frequency distribution of the data. (b) Wh...
 2.2.17E: In Determine the original set of data. Legend: 10 represents 10
 2.2.17: Free Throws A basketball player habitually makes 70% of her free th...
 2.2.18E: In Determine the original set of data. Legend: x240 represents 240
 2.2.18: In 1720, determine the original set of data.1 0 1 42 1 4 4 7 93 3 5...
 2.2.19E: In Determine the original set of data. Legend: 12 represents 1.2
 2.2.19: In 1720, determine the original set of data.24 0 4 725 2 2 3 9 926 ...
 2.2.20E: In Determine the original set of data. Legend: 123 represents 12.3
 2.2.20: In 1720, determine the original set of data.12 3 7 9 913 0 4 5 7 8 ...
 2.2.21E: In Find (a) the number of classes, (b) the class limits, and (c) th...
 2.2.21: In 2124, find (a) the number of classes, (b) the class limits, and ...
 2.2.22E: In Find (a) the number of classes, (b) the class limits, and (c) th...
 2.2.22: In 2124, find (a) the number of classes, (b) the class limits, and ...
 2.2.23E: In Find (a) the number of classes, (b) the class limits, and (c) th...
 2.2.23: In 2124, find (a) the number of classes, (b) the class limits, and ...
 2.2.24E: In Find (a) the number of classes, (b) the class limits, and (c) th...
 2.2.24: In 2124, find (a) the number of classes, (b) the class limits, and ...
 2.2.25E: In Problem, construct (a) a relative frequency distribution, a freq...
 2.2.25: In 2528, construct (a) a relative frequency distribution, (b) a fre...
 2.2.26E: In Problem, construct (a) a relative frequency distribution, a freq...
 2.2.26: In 2528, construct (a) a relative frequency distribution, (b) a fre...
 2.2.27E: In Problem, construct (a) a relative frequency distribution, a freq...
 2.2.27: In 2528, construct (a) a relative frequency distribution, (b) a fre...
 2.2.28E: In Problem, construct (a) a relative frequency distribution, a freq...
 2.2.28: In 2528, construct (a) a relative frequency distribution, (b) a fre...
 2.2.29E: Televisions in the Household A researcher with A. C. Nielsen wanted...
 2.2.29: Televisions in the Household A researcher with A. C. Nielsen wanted...
 2.2.30E: Waiting The data in the next column represent the number of custome...
 2.2.30: Waiting The data in the next column represent the number of custome...
 2.2.31E: Average Income The following data represent the per capita (average...
 2.2.31: Average Income The following data represent the per capita (average...
 2.2.32E: Uninsured Rates The following data represent the percentage of peop...
 2.2.32: Uninsured Rates The following data represent the percentage of peop...
 2.2.33E: Cigarette Tax Rates The table shows the tax, in dollars, on a pack ...
 2.2.33: . Cigarette Tax Rates The table shows the tax, in dollars, on a pac...
 2.2.34E: Dividend Yield A dividend is a payment from a publicly traded compa...
 2.2.34: . Dividend Yield A dividend is a payment from a publicly traded com...
 2.2.35E: Violent Crimes Violent crimes include murder, forcible rape, robber...
 2.2.35: Violent Crimes Violent crimes include murder, forcible rape, robber...
 2.2.36E: Volume of Altria Group Stock The volume of a stock is the number of...
 2.2.36: Volume of Altria Group Stock The volume of a stock is the number of...
 2.2.37E: In Problem, (a) construct a stemandleaf plot and describe the sha...
 2.2.37: In 3740, (a) construct a stemandleaf plot and (b) describe the sh...
 2.2.38E: Divorce Rates The following data represent the divorce rate (per 10...
 2.2.38: In 3740, (a) construct a stemandleaf plot and (b) describe the sh...
 2.2.39E: Grams of Fat in a McDonald’s Breakfast The following data represent...
 2.2.39: In 3740, (a) construct a stemandleaf plot and (b) describe the sh...
 2.2.40E: Gasoline Mileages The following data represent the number of miles ...
 2.2.40: In 3740, (a) construct a stemandleaf plot and (b) describe the sh...
 2.2.41E: Electric Rates The following data represent the average retail pric...
 2.2.41: Electric Rates The following data represent the average retail pric...
 2.2.42E: Home Appreciation The following data represent the price appreciati...
 2.2.42: Home Appreciation The following data represent the price appreciati...
 2.2.43E: Violent Crimes Use the violent crime rate data from answer each of ...
 2.2.43: Violent Crimes Use the violent crime rate data from to answer each ...
 2.2.44E: In Problem, we compare data sets. A great way to compare two data s...
 2.2.44: In 44 and 45, we compare data sets. A great way to compare two data...
 2.2.45E: Home Run Distances In 1998, Mark McGwire of the St. Louis Cardinals...
 2.2.45: In 44 and 45, we compare data sets. A great way to compare two data...
 2.2.46E: StatCrunch Survey Choose a discrete quantitative variable from the ...
 2.2.46: . StatCrunch Survey Choose a discrete quantitative variable from th...
 2.2.47E: StatCrunch Survey Choose a continuous quantitative variable from th...
 2.2.47: StatCrunch Survey Choose a continuous quantitative variable from th...
 2.2.48E: StatCrunch Survey Draw a dot plot of the variable “ideal number of ...
 2.2.48: . StatCrunch Survey Draw a dot plot of the variable ideal number of...
 2.2.49E: Televisions in the Household Draw a dot plot of the televisions per...
 2.2.49: Televisions in the Household Draw a dot plot of the televisions per...
 2.2.50E: Waiting Draw a dot plot of the waiting data from Problem. The data ...
 2.2.50: Waiting Draw a dot plot of the waiting data from 30.
 2.2.51E: Putting It Together: Time Viewing a Web Page Nielsen/NetRatings is ...
 2.2.51: Putting It Together: Time Viewing a Web Page Nielsen/ NetRatings is...
 2.2.52E: Putting It Together: Which Graphical Summary? Suppose you just obta...
 2.2.52: Putting It Together: Which Graphical Summary? Suppose you just obta...
 2.2.53E: Why shouldn’t classes overlap when summarizing continuous data in a...
 2.2.53: Why shouldnt classes overlap when summarizing continuous data in a ...
 2.2.54E: Discuss the advantages and disadvantages of histograms versus stem...
 2.2.54: Discuss the advantages and disadvantages of histograms versus stem...
 2.2.55E: Is there such a thing as the correct choice for a class width? Is t...
 2.2.55: Is there such a thing as the correct choice for a class width? Is t...
 2.2.56E: Describe the situations in which it is preferable to use relative f...
 2.2.56: Describe the situations in which it is preferable to use relative f...
 2.2.57E: StatCrunch Choose any data set that has at least 50 observations of...
 2.2.57: StatCrunch Choose any data set that has at least 50 observations of...
 2.2.58E: Sketch four histograms—one skewed right, one skewed left, one bell...
 2.2.58: Sketch four histogramsone skewed right, one skewed left, one bells...
Solutions for Chapter 2.2: ORGANIZING QUANTITATIVE DATA: THE POPULAR DISPLAYS
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 2.2: ORGANIZING QUANTITATIVE DATA: THE POPULAR DISPLAYS
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Chapter 2.2: ORGANIZING QUANTITATIVE DATA: THE POPULAR DISPLAYS includes 116 full stepbystep solutions. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4. Since 116 problems in chapter 2.2: ORGANIZING QUANTITATIVE DATA: THE POPULAR DISPLAYS have been answered, more than 161763 students have viewed full stepbystep solutions from this chapter.

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.

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Average
See Arithmetic mean.

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.

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.

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Continuous distribution
A probability distribution for a continuous random variable.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Contrast
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

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.

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 .

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.

Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.

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

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.

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.

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.

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 .

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .