- Chapter C.4.1AYU: The acronym ANOVA stands for.
- Chapter C.4.2AYU: True or False: To perform a one-way ANOVA, the populations do not n...
- Chapter C.4.3AYU: True or False: To perform a one-way ANOVA, the populations must hav...
- Chapter C.4.4AYU: The variability among the sample means is called-sample variability...
- Chapter C.4.5AYU: The variability within each treatment group, which is a weighted av...
- Chapter C.4.6AYU: True or False: The F-test statistic is F0 =
- Chapter C.4.7AYU: fill in the ANOVA table.
- Chapter C.4.8AYU: fill in the ANOVA table.
- Chapter C.4.9AYU: determine the F-test statistic based on the given summary statistic...
- Chapter C.4.10AYU: determine the F-test statistic based on the given summary statistic...
- Chapter C.4.11AYU: The following data represent a simple random sample of n = 4 from t...
- Chapter C.4.12AYU: The following data represent a simple random sample of n = 5 from t...
- Chapter C.4.13AYU: Corn Production The data in the table represent the number of corn ...
- Chapter C.4.14AYU: Soybean Yield The data in the table represent the number of pods on...
- Chapter C.4.15AYU: Which Delivery Method Is Best? At a community college, the mathemat...
- Chapter C.4.16AYU: Births by Day of Week An obstetrician knew that there were more liv...
- Chapter C.4.17AYU: Rates of Return A stock analyst wondered whether the mean rate of r...
- Chapter C.4.18AYU: Reaction Time In an online psychology experiment sponsored by the U...
- Chapter C.4.19AYU: Car-Buying Discrimination To determine if there is gender and/or ra...
- Chapter C.4.20AYU: Crash Data The Insurance Institute for Highway Safety conducts expe...
- Chapter C.4.21AYU: pH in Rain An environmentalist wanted to determine if the mean acid...
- Chapter C.4.22AYU: Lower Your Cholesterol Researchers Francisco Fuentes and his collea...
- Chapter C.4.23AYU: Sullivan Statistics Survey: What Is Rich? Treat the results of the ...
- Chapter C.4.24AYU: Sullivan Statistics Survey: Age and Politics Do people’s political ...
- Chapter C.4.25AYU: Concrete Strength An engineer wants to know if the mean strengths o...
- Chapter C.4.26AYU: Analyzing Journal Article Results Researchers (Brian G. Feagan et a...
- Chapter C.4.27AYU: Putting It Together: Psychological Profiles Researchers wanted to d...
- Chapter C.4.28AYU: What are the requirements to perform a one-way ANOVA? Is the test r...
- Chapter C.4.29AYU: What is the mean square due to treatment estimate of ?2? What is th...
- Chapter C.4.30AYU: Why does a large value of the F statistic provide evidence against ...
- Chapter C.4.31AYU: In a one-way ANOVA, explain what it means to reject the statement i...
Solutions for Chapter Chapter C.4: Fundamentals of Statistics 4th Edition
Full solutions for Fundamentals of Statistics | 4th Edition
`-error (or `-risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).
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).
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
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.
See Arithmetic mean.
Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain
A distribution with two modes
Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.
Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
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.
Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.
Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.
Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.
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.
Exponential random variable
A series of tests in which changes are made to the system under study
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.