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# Solutions for Chapter 9-2: 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 9-2: Testing the Difference Between Two Means of Independent Samples: Using the t Test

Solutions for Chapter 9-2
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##### ISBN: 9780073386102

This 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 9-2: Testing the Difference Between Two Means of Independent Samples: Using the t Test includes 18 full step-by-step solutions. Since 18 problems in chapter 9-2: Testing the Difference Between Two Means of Independent Samples: Using the t Test have been answered, more than 34198 students have viewed full step-by-step solutions from this chapter.

Key Statistics Terms and definitions covered in this textbook
• 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

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