 13.2.1 BSC: ?Sign Test for Freshman 15 The table below lists some of the weight...
 13.2.2 BSC: ?Identifying Signs For the sign test described in Exercise 1, ident...
 13.2.3 BSC: ?Contradicting H 1 An important step in conducting the sign test is...
 13.2.4 BSC: Efficiency of the Sign Test Refer to Table 132 in Section 131 and...
 13.2.5 BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.6 BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.7 BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.8 BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.9 BSC: ?Oscar Winners Listed below are ages of actresses and actors at the...
 13.2.10 BSC: ?Oscar Winners Repeat Exercise 9 using all of the 82 pairs of ages ...
 13.2.11 BSC: Use the sign test for the data consisting of matched pairs.Heights ...
 13.2.12 BSC: ?Flight Data Repeat Example 2 using the following times for America...
 13.2.13 BSC: Use the sign test for the claim involving nominal data.Gender Selec...
 13.2.14 BSC: Use the sign test for the claim involving nominal data.Predicting S...
 13.2.15 BSC: Use the sign test for the claim involving nominal data.Touch Therap...
 13.2.16 BSC: Use the sign test for the claim involving nominal data.Football Sur...
 13.2.17 BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.18 BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.19 BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.20 BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.21 BB: Procedures for Handling Ties In the sign test procedure described i...
 13.2.22 BB: Finding Critical Values Table A7 lists critical values for limited...
 13.2.1BSC: Sign Test for Freshman 15?The table below lists some of the weights...
 13.2.2BSC: Identifying Signs?For the sign test described in Exercise?,?identif...
 13.2.3BSC: Contradicting? ?H?1?An important step in conducting the sign test i...
 13.2.4BSC: Efficiency of the Sign TestRefer to Table 132 in Section 131 and ...
 13.2.5BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.6BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.7BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.8BSC: Assume that matched pairs of data result in the given number of sig...
 13.2.9BSC: Use the sign test for the data consisting of matched pairs. Oscar W...
 13.2.10BSC: Use the sign test for the data consisting of matched pairs. Oscar W...
 13.2.11BSC: Use the sign test for the data consisting of matched pairs. Heights...
 13.2.12BSC: Use the sign test for the data consisting of matched pairs. Flight ...
 13.2.13BSC: Use the sign test for the claim involving nominal data. Gender Sele...
 13.2.14BSC: Use the sign test for the claim involving nominal data. Predicting ...
 13.2.15BSC: Use the sign test for the claim involving nominal data. Touch Thera...
 13.2.16BSC: Use the sign test for the claim involving nominal data. Football Su...
 13.2.17BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.18BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.19BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.20BSC: Refer to the indicated data set in Appendix B and use the sign test...
 13.2.21BB: Procedures for Handling Ties In the sign test procedure described i...
 13.2.22BB: Finding Critical Values Table A7 lists critical values for limited...
Solutions for Chapter 13.2: Elementary Statistics 12th Edition
Full solutions for Elementary Statistics  12th Edition
ISBN: 9780321836960
Solutions for Chapter 13.2
Get Full SolutionsElementary Statistics was written by and is associated to the ISBN: 9780321836960. This textbook survival guide was created for the textbook: Elementary Statistics, edition: 12. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 13.2 includes 44 full stepbystep solutions. Since 44 problems in chapter 13.2 have been answered, more than 356702 students have viewed full stepbystep solutions from this chapter.

Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability

Bivariate distribution
The joint probability distribution of two random variables.

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.

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.

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 variance.
The variance of the conditional probability distribution of a random variable.

Conidence interval
If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

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 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 .

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

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

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.

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

Fisher’s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

Geometric mean.
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .