- 8.1.1: Statistical Literacy The value zc is a value from the standard norm...
- 8.1.2: Statistical Literacy The point estimate for the population mean m o...
- 8.1.3: Statistical Literacy Consider a random sample of size n from an x d...
- 8.1.4: Statistical Literacy Every random sample of the same size from a gi...
- 8.1.5: Statistical Literacy A larger sample size produces a longer confide...
- 8.1.6: Statistical Literacy If the original x distribution has a relativel...
- 8.1.7: Statistical Literacy If the sample mean of a random sample from an ...
- 8.1.8: Statistical Literacy For the same random sample, when the confidenc...
- 8.1.9: Critical Thinking Sam computed a 95% confidence interval for m from...
- 8.1.10: Critical Thinking Sam computed a 90% confidence interval for m from...
- 8.1.11: Zoology: Hummingbirds Allens hummingbird (Selasphorus sasin) has be...
- 8.1.12: Diagnostic Tests: Uric Acid Overproduction of uric acid in the body...
- 8.1.13: Diagnostic Tests: Plasma Volume Total plasma volume is important in...
- 8.1.14: Agriculture: Watermelon What price do farmers get for their waterme...
- 8.1.15: FBI Report: Larceny Thirty small communities in Connecticut (popula...
- 8.1.16: Salaries: Student Services Consider college officials in admissions...
- 8.1.17: Salaries: College Administrators How much do college administrators...
- 8.1.18: Ecology: Sand Dunes At wind speeds above 1000 centimeters per secon...
- 8.1.19: Profits: Banks Jobs and productivity! How do banks rate? One way to...
- 8.1.20: Profits: Retail Jobs and productivity! How do retail stores rate? O...
- 8.1.21: Ballooning: Air Temperature How hot is the air in the top (crown) o...
Solutions for Chapter 8.1: ESTIMATION
Full solutions for Understandable Statistics | 9th Edition
In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion
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
See Arithmetic mean.
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.
The joint probability distribution of two random variables.
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.
Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
The variance of the conditional probability distribution of a random variable.
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
Another term for the conidence coeficient.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.
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 measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .
A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.
Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.
A study in which a sample from a population is used to make inference to the population. See Analytic study
Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.
A model that contains only irstorder terms. For example, the irst-order response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irst-order model is also called a main effects model
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