×
Log in to StudySoup
Get Full Access to Statistics - Textbook Survival Guide
Join StudySoup for FREE
Get Full Access to Statistics - Textbook Survival Guide
×
Reset your password

# Solutions for Chapter 8.2: Testing the Difference Between Means (Independent Samples, s1 and s2 Unknown)

## Full solutions for Elementary Statistics: Picturing the World | 6th Edition

ISBN: 9780321911216

Solutions for Chapter 8.2: Testing the Difference Between Means (Independent Samples, s1 and s2 Unknown)

Solutions for Chapter 8.2
4 5 0 288 Reviews
23
5
##### ISBN: 9780321911216

Since 26 problems in chapter 8.2: Testing the Difference Between Means (Independent Samples, s1 and s2 Unknown) have been answered, more than 109625 students have viewed full step-by-step solutions from this chapter. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321911216. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World , edition: 6. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 8.2: Testing the Difference Between Means (Independent Samples, s1 and s2 Unknown) includes 26 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
• Acceptance region

In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

• 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

• Binomial random variable

A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

• Box plot (or box and whisker plot)

A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

• C chart

An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

• Cause-and-effect diagram

A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

• Chi-square (or chi-squared) random variable

A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.

• Correction factor

A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

• Counting techniques

Formulas used to determine the number of elements in sample spaces and events.

• Cumulative normal distribution function

The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

• Curvilinear regression

An expression sometimes used for nonlinear regression models or polynomial regression models.

• Designed experiment

An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

• 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).

• Distribution function

Another name for a cumulative distribution function.

• Empirical model

A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

• Enumerative study

A study in which a sample from a population is used to make inference to the population. See Analytic study

• Error sum of squares

In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a model-itting process and not on replication.

• Error variance

The variance of an error term or component in a model.

• False alarm

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

• Gaussian distribution

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

×
Log in to StudySoup
Get Full Access to Statistics - Textbook Survival Guide
Join StudySoup for FREE
Get Full Access to Statistics - Textbook Survival Guide
×
Reset your password