- 5.3.8E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.9E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.10E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.11E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.13E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.14E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.15E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.16E: assume all variables are binomial. (Note: If values are not found i...
- 5.3.19E: Social Security Recipients A study found that 1 % of Social Securit...
- 5.3.20E: Tossing Coins Find the mean, variance, and standard deviation for t...
- 5.3.22E: Federal Government Employee E-mail Use It has been reported that 83...
- 5.3.23E: Watching Fireworks A survey found that 21 % of Americans watch fire...
- 5.3.24E: Alternate Sources of Fuel Eighty-five percent of Americans favor sp...
- 5.3.25E: Survey on Bathing Pets A survey found that 25% of pet owners had th...
- 5.3.26E: Survey on Answering Machine Ownership In a survey, 63% of Americans...
- 5.3.27E: Poverty and the Federal Government One out of every three Americans...
- 5.3.28E: Internet Purchases Thirty-two percent of adult Internet users have ...
- 5.3.31E: Survey of High School Seniors Of graduating high school seniors, 14...
- 5.3.32E: Is this a binomial distribution? Explain.X0123P(X)0.0640.2880.4320.216
- 5.3.33EC: Children in a Family The graph shown here represents the probabilit...
- 5.3.34EC: Construct a binomial distribution graph for the number of defective...
Solutions for Chapter 5.3: Elementary Statistics: A Step By Step Approach 9th Edition
Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).
Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation
Bivariate normal distribution
The joint distribution of two normal random variables
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.
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 .
Formulas used to determine the number of elements in sample spaces and events.
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment
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).
Another name for a cumulative distribution function.
A subset of a sample space.
A property of a collection of events that indicates that their union equals the sample space.
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.
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.
In statistical quality control, that portion of a number of units or the output of a process that is defective.
Fraction defective control chart
See P chart
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.
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on
Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function