 1.2.1CSE: Rating Points Each rating point represents 1,142,000 households, or...
 1.2.1E: Name each level of measurement for which data can be qualitative.
 1.2.2CSE: Sampling Percent What percentage of the total number of U.S. househ...
 1.2.2E: Name each level of measurement for which data can be quantitative.
 1.2.3CSE: Nominal Level of Measurement Identify any column(s) in the table wi...
 1.2.3E: True or False? In Exercise, determine whether the statement is true...
 1.2.4CSE: Ordinal Level of Measurement Identify any column(s) in the table wi...
 1.2.4E: True or False? In Exercise, determine whether the statement is true...
 1.2.5CSE: Interval Level of Measurement Identify any column(s) in the table w...
 1.2.5E: True or False? In Exercise, determine whether the statement is true...
 1.2.6CSE: Ratio Level of Measurement Identify any column(s) in the table with...
 1.2.6E: True or False? In Exercise, determine whether the statement is true...
 1.2.7CSE: Rankings How are the programs ranked in the table? Why do you think...
 1.2.8CSE: Inferences What decisions (inferences) can be made on the basis of ...
 1.2.8E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.10E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.12E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.14E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.15E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.16E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.17E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.18E: Classifying Data by Type In Exercise, determine whether the data ar...
 1.2.21E: Classifying Data by Type and Level In Exercise, determine whether t...
 1.2.29E: The items below appear on an employment application. Determine the ...
 1.2.30E: The items below appear on an employment application. Determine the ...
Solutions for Chapter 1.2: Elementary Statistics: Picturing the World 5th Edition
Full solutions for Elementary Statistics: Picturing the World  5th Edition
ISBN: 9780321693624
Solutions for Chapter 1.2
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Chapter 1.2 includes 25 full stepbystep solutions. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321693624. Since 25 problems in chapter 1.2 have been answered, more than 11213 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World, edition: 5.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

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

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.

Central tendency
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

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.

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.

Curvilinear regression
An expression sometimes used for nonlinear regression models or polynomial regression models.

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

Design matrix
A matrix that provides the tests that are to be conducted in an experiment.

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.

Estimate (or point estimate)
The numerical value of a point estimator.

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.

Gamma function
A function used in the probability density function of a gamma random variable that can be considered to extend factorials

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.

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.