 92.1: Bestseller Books The mean for the number of weeks 15 New York Times...
 92.2: TaxExempt Properties A tax collector wishes to see if the mean val...
 92.3: Noise Levels in Hospitals The mean noise level of 20 areas designat...
 92.4: Ages of Gamblers The mean age of a sample of 25 people who were pla...
 92.5: Carbohydrates in Candies The number of grams of carbohydrates conta...
 92.6: Teacher Salaries A researcher claims that the mean of the salaries ...
 92.7: Weights of Running Shoes The weights in ounces of a sample of runni...
 92.8: Weights of Vacuum Cleaners Upright vacuum cleaners have either a ha...
 92.9: Find the 95% confidence interval for the difference of the means in...
 92.10: Find the 95% confidence interval for the difference of the means in...
 92.11: Hours Spent Watching Television According to Nielsen Media Research...
 92.12: NFL Salaries An agent claims that there is no difference between th...
 92.13: Cyber School Enrollment The data show the number of students attend...
 92.14: Ages of Homes Whiting, Indiana, leads the Top 100 Cities with the O...
 92.15: Hospital Stays for Maternity Patients Health Care Knowledge Systems...
 92.16: Hockeys Highest Scorers The number of points held by a sample of th...
 92.17: Medical School Enrollments A random sample of enrollments from medi...
 92.18: OutofState Tuitions The outofstate tuitions (in dollars) for ra...
Solutions for Chapter 92: Testing the Difference Between Two Means of Independent Samples: Using the t Test
Full solutions for Elementary Statistics: A Step by Step Approach 8th ed.  8th Edition
ISBN: 9780073386102
Solutions for Chapter 92: Testing the Difference Between Two Means of Independent Samples: Using the t Test
Get Full SolutionsThis textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 92: Testing the Difference Between Two Means of Independent Samples: Using the t Test includes 18 full stepbystep solutions. Since 18 problems in chapter 92: Testing the Difference Between Two Means of Independent Samples: Using the t Test have been answered, more than 34198 students have viewed full stepbystep solutions from this chapter.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

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

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.

Biased estimator
Unbiased estimator.

Bivariate distribution
The joint probability distribution of two random variables.

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Conditional mean
The mean of the conditional probability distribution of a random variable.

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

Conditional variance.
The variance of the conditional probability distribution of a 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.

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

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

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.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Density function
Another name for a probability density function

Discrete distribution
A probability distribution for a discrete random variable

Dispersion
The amount of variability exhibited by data

Estimate (or point estimate)
The numerical value of a point estimator.

False alarm
A signal from a control chart when no assignable causes are present