 7.1.1E: What is the difference between a point estimate and an interval est...
 7.1.2E: What information is necessary to calculate a confidence interval?
 7.1.3E: What is the margin of error?
 7.1.4E: What is meant by the 95% confidence interval of the mean?
 7.1.5E: What are three properties of a good estimator?
 7.1.6E: What statistic best estimates ??
 7.1.7E: Find each.a. za/2 for the 99% confidence interval________________b....
 7.1.8E: What is necessary to determine the sample size?
 7.1.11E: Playing Video GamesIn a recent study of 35 ninth grade students, t...
 7.1.12E: Number of JobsA sociologist found that in a sample of 50 retired me...
 7.1.13E: Number of FacultyThe numbers of faculty at 32 randomly selected sta...
 7.1.14E: Freshmen’s GPAFirstsemester GPAs for a random selection of freshme...
 7.1.16E: Number of Farms A random sample of the number of farms (in thousand...
 7.1.18E: Day Care Tuition A random sample of 50 fouryearolds attending day...
 7.1.19E: Hospital Noise Levels Noise levels at various area urban hospitals ...
 7.1.23E: Birth Weights of InfantsA health care professional wishes to estima...
 7.1.24E: Cost of Pizzas A pizza shop owner wishes to find the 95% confidence...
 7.1.25E: National Accounting Examination If the variance of a national accou...
Solutions for Chapter 7.1: Elementary Statistics: A Step By Step Approach 9th Edition
Full solutions for Elementary Statistics: A Step By Step Approach  9th Edition
ISBN: 9780073534985
Solutions for Chapter 7.1
Get Full SolutionsThis textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9. Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 7.1 includes 18 full stepbystep solutions. Since 18 problems in chapter 7.1 have been answered, more than 192291 students have viewed full stepbystep solutions from this chapter.

Alias
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Average
See Arithmetic mean.

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Bimodal distribution.
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.

Central tendency
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

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.

Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.

Confounding
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

Correlation
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 distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

Defect
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.

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).

Factorial experiment
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

Gamma function
A function used in the probability density function of a gamma random variable that can be considered to extend factorials