- 9.1.1: Statistical Literacy Discuss each of the following topics in class ...
- 9.1.2: Statistical Literacy In a statistical test, we have a choice of a l...
- 9.1.3: Statistical Literacy If we fail to reject (i.e., accept) the null h...
- 9.1.4: Statistical Literacy If we reject the null hypothesis, does this me...
- 9.1.5: Veterinary Science: Colts The body weight of a healthy 3-month-old ...
- 9.1.6: Marketing: Shopping Time How much customers buy is a direct result ...
- 9.1.7: Meteorology: Storms Weatherwise magazine is published in associatio...
- 9.1.8: Chrysler Concorde: Acceleration Consumer Reports stated that the me...
- 9.1.9: Dividend Yield: Australian Bank Stocks Let x be a random variable r...
- 9.1.10: Glucose Level: Horses Gentle Ben is a Morgan horse at a Colorado du...
- 9.1.11: Ecology: Hummingbirds Bill Alther is a zoologist who studies Annas ...
- 9.1.12: Finance: P/E of Stocks The price to earnings ratio (P/E) is an impo...
- 9.1.13: Insurance: Hail Damage Nationally, about 11% of the total U.S. whea...
- 9.1.14: Medical: Red Blood Cell Volume Total blood volume (in ml) per body ...
Solutions for Chapter 9.1: HYPOTHESIS TESTING
Full solutions for Understandable Statistics | 9th Edition
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
A distribution with two modes
Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.
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 probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables
Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.
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 off-diagonal elements rij are the correlations between Xi and Xj .
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 off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.
Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t
An expression sometimes used for nonlinear regression models or polynomial regression models.
Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.
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).
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.
Any test of signiicance involving the F distribution. The most common F-tests 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.
In statistical quality control, that portion of a number of units or the output of a process that is defective.
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function
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 .