- 7.1.1E: What is the difference between a point estimate and an interval est...
- 7.1.2E: What information is necessary to calculate a confidence interval?
- 7.1.3E: What is the margin of error?
- 7.1.4E: What is meant by the 95% confidence interval of the mean?
- 7.1.5E: What are three properties of a good estimator?
- 7.1.6E: What statistic best estimates ??
- 7.1.7E: Find each.a. za/2 for the 99% confidence interval________________b....
- 7.1.8E: What is necessary to determine the sample size?
- 7.1.11E: Playing Video GamesIn a recent study of 35 ninth- grade students, t...
- 7.1.12E: Number of JobsA sociologist found that in a sample of 50 retired me...
- 7.1.13E: Number of FacultyThe numbers of faculty at 32 randomly selected sta...
- 7.1.14E: Freshmen’s GPAFirst-semester GPAs for a random selection of freshme...
- 7.1.16E: Number of Farms A random sample of the number of farms (in thousand...
- 7.1.18E: Day Care Tuition A random sample of 50 four-year-olds attending day...
- 7.1.19E: Hospital Noise Levels Noise levels at various area urban hospitals ...
- 7.1.23E: Birth Weights of InfantsA health care professional wishes to estima...
- 7.1.24E: Cost of Pizzas A pizza shop owner wishes to find the 95% confidence...
- 7.1.25E: National Accounting Examination If the variance of a national accou...
Solutions for Chapter 7.1: Elementary Statistics: A Step By Step Approach 9th Edition
Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition
a-error (or a-risk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.
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.
Average run length, or ARL
The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.
Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
Bivariate normal distribution
The joint distribution of two normal random variables
Coeficient of determination
See R 2 .
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.
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).
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
Another name for a probability density function
A probability distribution for a discrete random variable
Estimate (or point estimate)
The numerical value of a point estimator.
Extra sum of squares method
A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.
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.
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.
Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r