- 2.2.1E: DNA molecules consist of chemically linked sequences of the bases a...
- 2.2.2E: A metallurgist is designing an experiment to determine the effect o...
- 2.2.3E: The article “Improved Bioequivalence Assessment of Topical Dermatol...
- 2.2.4E: A group of 18 people have gotten together to play baseball. They wi...
- 2.2.5E: In horse racing, one can make a trifecta bet by specifying which ho...
- 2.2.6E: A college math department consisting of 10 faculty members must cho...
- 2.2.7E: A test consists of 15 questions. Ten are true-false questions, and ...
- 2.2.8E: In a certain state, license plates consist of three letters followe...
- 2.2.9E: A computer password consists of eight characters.a. How many differ...
- 2.2.10E: A company has hired 15 new employees, and must assign 6 to the day ...
- 2.2.11E: One drawer in a dresser contains 8 blue socks and 6 white socks. A ...
- 2.2.12E: A drawer contains 6 red socks, 4 green socks, and 2 black socks. Tw...
Solutions for Chapter 2.2: Statistics for Engineers and Scientists 4th Edition
Full solutions for Statistics for Engineers and Scientists | 4th 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).
See Arithmetic mean.
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
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.
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.
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 mean of the conditional probability distribution of a random variable.
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.
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.
A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.
Defects-per-unit control chart
See U chart
The amount of variability exhibited by data
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
The variance of an error term or component in a model.
Estimate (or point estimate)
The numerical value of a point estimator.
The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.
In statistical quality control, that portion of a number of units or the output of a process that is defective.