- 12-2.1: What two tests can be used to compare two means when the null hypot...
- 12-2.2: Explain the difference between the two tests used to compare two me...
- 12-2.3: Exercise 9 in Section 121.
- 12-2.4: Exercise 12 in Section 121.
- 12-2.5: Exercise 13 in Section 121.
- 12-2.6: Exercise 16 in Section 121. No further testing should be done.
- 12-2.7: Exercise 17 in Section 121.
- 12-2.8: Exercise 18 in Section 121.
- 12-2.9: Exercise 20 in Section 121.
- 12-2.10: Weights of Digital Cameras The data consist of the weights in ounce...
- 12-2.11: Fiber Content of Foods The number of grams of fiber per serving for...
- 12-2.12: Per-Pupil Expenditures The expenditures (in dollars) per pupil for ...
- 12-2.13: Weekly Unemployment Benefits The average weekly unemployment benefi...
Solutions for Chapter 12-2: The Scheff Test and the Tukey Test
Full solutions for Elementary Statistics: A Step by Step Approach 8th ed. | 8th 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
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.
Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data
Coeficient of determination
See R 2 .
The probability of an event given that the random experiment produces an outcome in another event.
A probability distribution for a continuous random variable.
Formulas used to determine the number of elements in sample spaces and events.
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.
Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.
The variance of an error term or component in a model.
Estimate (or point estimate)
The numerical value of a point estimator.
Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.
In statistical quality control, that portion of a number of units or the output of a process that is defective.
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
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .
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 .