- 8-1.1: What prompted the study?
- 8-1.2: What is the population under study?
- 8-1.3: Was a sample collected?
- 8-1.4: What was the hypothesis?
- 8-1.5: Were data collected?
- 8-1.6: Were any statistical tests run?
- 8-1.7: What was the conclusion?
- 8-1.8: Explain what is meant by a significant difference
- 8-1.9: When should a one-tailed test be used? A two-tailed test?
- 8-1.10: List the steps in hypothesis testing.
- 8-1.11: In hypothesis testing, why cant the hypothesis be proved true?
- 8-1.12: Using the z table (Table E), find the critical value (or values) fo...
- 8-1.13: For each conjecture, state the null and alternative hypotheses. a. ...
Solutions for Chapter 8-1: Hypothesis Testing
Full solutions for Elementary Statistics: A Step by Step Approach | 7th 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).
Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.
Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.
Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.
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
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.
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.
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.
Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.
A subset of effects in a fractional factorial design that deine the aliases in the design.
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.
Discrete random variable
A random variable with a inite (or countably ininite) range.
A study in which a sample from a population is used to make inference to the population. See Analytic study
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
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 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.
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 .
Having trouble accessing your account? Let us help you, contact support at +1(510) 944-1054 or email@example.com
Forgot password? Reset it here