 3.1.1: What does it mean if a statistic is resistant?
 3.1.1E: What does it mean if a statistic is resistant?
 3.1.2: In the 2009 Current Population Survey conducted by the U.S. Census ...
 3.1.2E: In the 2009 Current Population Survey conducted by the U.S. Census ...
 3.1.3: The U.S. Department of Housing and Urban Development (HUD) uses the...
 3.1.3E: The U.S. Department of Housing and Urban Development (HUD) uses the...
 3.1.4: A histogram of a set of data indicates that the distribution of the...
 3.1.4E: A histogram of a set of data indicates that the distribution of the...
 3.1.5: If a data set contains 10,000 values arranged in increasing order, ...
 3.1.5E: If a data set contains 10,000 values arranged in increasing order, ...
 3.1.6: True or False : A data set will always have exactly one mode.
 3.1.6E: True or False : A data set will always have exactly one mode.
 3.1.7: In 710, find the population mean or sample mean as indicated Sample...
 3.1.7E: Find the population mean or sample mean as indicated.Sample: 20, 13...
 3.1.8: In 710, find the population mean or sample mean as indicated Sample...
 3.1.8E: Find the population mean or sample mean as indicated.Sample: 83, 65...
 3.1.9: In 710, find the population mean or sample mean as indicated Popula...
 3.1.9E: Find the population mean or sample mean as indicated.Population: 3,...
 3.1.10: In 710, find the population mean or sample mean as indicated Popula...
 3.1.10E: Find the population mean or sample mean as indicated.Population: 1,...
 3.1.11: For Super Bowl XLIV, CBS television sold 55 ad slots for a total re...
 3.1.11E: For Super Bowl XLIV, CBS television sold 55 ad slots for a total re...
 3.1.12: The median for the given set of six ordered data values is 26.5. Wh...
 3.1.12E: The median for the given set of six ordered data values is 26.5. Wh...
 3.1.13: Crash Test Results The Insurance Institute for Highway Safety crash...
 3.1.13E: Crash Test Results The Insurance Institute for Highway Safety crash...
 3.1.14: Cell Phone Use The following data represent the monthly cell phone ...
 3.1.14E: Cell Phone Use The following data represent the monthly cell phone ...
 3.1.15: Concrete Mix A certain type of concrete mix is designed to withstan...
 3.1.15E: Concrete Mix A certain type of concrete mix is designed to withstan...
 3.1.16: Flight Time The following data represent the flight time (in minute...
 3.1.16E: Flight Time The following data represent the flight time (in minute...
 3.1.17: For each of the three histograms shown, determine whether the mean ...
 3.1.17E: For each of the three histograms shown, determine whether the mean ...
 3.1.18: Match the histograms shown to the summary statistics: Mean Median I...
 3.1.18E: Match the histograms shown to the summary statistics: MeanMedianI42...
 3.1.19: pH in Water The acidity or alkalinity of a solution is measured usi...
 3.1.19E: pH in Water The acidity or alkalinity of a solution is measured usi...
 3.1.20: Reaction Time In an experiment conducted online at the University o...
 3.1.20E: Reaction Time In an experiment conducted online at the University o...
 3.1.21: Pulse Rates The following data represent the pulse rates (beats per...
 3.1.21E: Pulse Rates The following data represent the pulse rates (beats per...
 3.1.22: Travel Time The following data represent the travel time (in minute...
 3.1.22E: Travel Time The following data represent the travel time (in minute...
 3.1.23: Carbon Dioxide Emissions The given data represent the fossilfuel c...
 3.1.23E: Carbon Dioxide Emissions The given data represent the fossilfuel c...
 3.1.24: Tour de Lance Lance Armstrong won the Tour de France seven consecut...
 3.1.24E: Tour de Lance Lance Armstrong won the Tour de France seven consecut...
 3.1.25: Connection Time A histogram of the connection time, in seconds, to ...
 3.1.25E: Connection Time A histogram of the connection time, in seconds, to ...
 3.1.26: . Journal Costs A histogram of the annual subscription cost (in dol...
 3.1.26E: Journal Costs A histogram of the annual subscription cost (in dolla...
 3.1.27: M&Ms The following data represent the weights (in grams) of a simpl...
 3.1.27E: M&Ms The following data represent the weights (in grams) of a simpl...
 3.1.28: Old Faithful We have all heard of the Old Faithful geyser in Yellow...
 3.1.28E: Old Faithful We have all heard of the Old Faithful geyser in Yellow...
 3.1.29: Hours Working A random sample of 25 college students was asked, How...
 3.1.29E: Hours Working A random sample of 25 college students was asked, “Ho...
 3.1.30: A Dealers Profit The following data represent the profit (in dollar...
 3.1.30E: A Dealer’s Profit The following data represent the profit (in dolla...
 3.1.31: Political Views A sample of 30 registered voters was surveyed in wh...
 3.1.31E: Political Views A sample of 30 registered voters was surveyed in wh...
 3.1.32: Hospital Admissions The following data represent the diagnosis of a...
 3.1.32E: Hospital Admissions The following data represent the diagnosis of a...
 3.1.33: Resistance and Sample Size Each of the following three data sets re...
 3.1.33E: Resistance and Sample Size Each of the following three data sets re...
 3.1.34: Mr. Zuro finds the mean height of all 14 students in his statistics...
 3.1.34E: Mr. Zuro finds the mean height of all 14 students in his statistics...
 3.1.35: Missing Exam Grade A professor has recorded exam grades for 20 stud...
 3.1.35E: Missing Exam Grade A professor has recorded exam grades for 20 stud...
 3.1.36: Survival Rates Unfortunately, a friend of yours has been diagnosed ...
 3.1.36E: Survival Rates Unfortunately, a friend of yours has been diagnosed ...
 3.1.37: Sullivan Survey Choose any quantitative variable from the Sullivan ...
 3.1.37E: Sullivan Survey Choose any quantitative variable from the Sullivan ...
 3.1.38: Sullivan Survey Choose any quantitative variable from the Sullivan ...
 3.1.38E: Sullivan Survey Choose any quantitative variable from the Sullivan ...
 3.1.39: Linear Transformations Benjamin owns a small Internet business. Bes...
 3.1.39E: Linear Transformations Benjamin owns a small Internet business. Bes...
 3.1.40: Linear Transformations Use the five test scores of 65, 70, 71, 75, ...
 3.1.40E: Linear Transformations Use the five test scores of 65, 70, 71, 75, ...
 3.1.41: Trimmed Mean Another measure of central tendency is the trimmed mea...
 3.1.41E: Trimmed Mean Another measure of central tendency is the trimmed mea...
 3.1.42: Midrange The midrange is also a measure of central tendency. It is ...
 3.1.42E: Midrange The midrange is also a measure of central tendency. It is ...
 3.1.43: Putting It Together: Shape, Mean and Median As part of a semester p...
 3.1.43E: Putting It Together: Shape, Mean and MedianAs part of a semester pr...
 3.1.44: FICO Scores The Fair Isaacs Corporation has devised a model that is...
 3.1.44E: FICO Scores The Fair Isaacs Corporation has devised a model that is...
 3.1.45: Why is the median resistant, but the mean is not?
 3.1.45E: Why is the median resistant, but the mean is not?
 3.1.46: A researcher with the Department of Energy wants to determine the m...
 3.1.46E: A researcher with the Department of Energy wants to determine the m...
 3.1.47: Net Worth According to the Statistical Abstract of the United State...
 3.1.47E: Net Worth According to the Statistical Abstract of the United State...
 3.1.48: You are negotiating a contract for the Players Association of the N...
 3.1.48E: You are negotiating a contract for the Players Association of the N...
 3.1.49: In January 2011, the mean amount of money lost per visitor to a loc...
 3.1.49E: In January 2011, the mean amount of money lost per visitor to a loc...
 3.1.50: For each of the following situations, determine which measure of ce...
 3.1.50E: For each of the following situations, determine which measure of ce...
Solutions for Chapter 3.1: MEASURES OF CENTRAL TENDENCY
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 3.1: MEASURES OF CENTRAL TENDENCY
Get Full SolutionsSince 100 problems in chapter 3.1: MEASURES OF CENTRAL TENDENCY have been answered, more than 145125 students have viewed full stepbystep solutions from this chapter. Chapter 3.1: MEASURES OF CENTRAL TENDENCY includes 100 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. This expansive textbook survival guide covers the following chapters and their solutions.

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

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

Attribute control chart
Any control chart for a discrete random variable. See Variables 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.

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

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.

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

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

Correction factor
A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

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.

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

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

Dispersion
The amount of variability exhibited by data

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).

Error sum of squares
In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a modelitting process and not on replication.

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

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.