 11.5.1: A researcher wanted to determine the effectiveness of a new cream i...
 11.5.2: A random sample of n1 = 120 individuals results in x1 = 43 successe...
 11.5.3: If n1 = 31, s1 = 12, n2 = 51, and s2 = 10, test whether s1 7 s2 at ...
 11.5.4: If n1 = 31, s1 = 12, n2 = 51, and s2 = 10, test whether s1 7 s2 at ...
 11.5.5: A random sample of n1 = 135 individuals results in x1 = 40 successe...
 11.5.6: If n1 = 61, s1 = 18.3, n2 = 57, and s2 = 13.5, test whether the pop...
 11.5.7: A random sample of size n = 41 results in a sample mean of 125.3 an...
 11.5.8: The following data represent the measure of a variable before and a...
 11.5.9: The following data represent the measure of a variable before and a...
 11.5.10: Conduct the appropriate test to determine if the population proport...
 11.5.11: Collision Claims Automobile collision insurance is used to pay for ...
 11.5.12: TIMS Report and Kumon TIMS is an acronym for the Third Internationa...
 11.5.13: Health and Happiness In a General Social Survey, adult Americans we...
 11.5.14: Cash or Credit? Do people tend to spend more money on fastfood whe...
 11.5.15: Walmart versus Target Is there a difference in the pricing at Walma...
 11.5.16: Predicting Election Outcomes Researchers Alexander Todorov and asso...
 11.5.17: Gas Prices in Chicago In January 2011, the national mean price per ...
 11.5.18: Bribe em with Chocolate In a study published in the journal Teachin...
 11.5.19: Unwed Women Having Children The Pew Research Group asked the follow...
 11.5.20: Volume of Stock The daily volume of a stock represents the total nu...
 11.5.21: Comparing Rates of Return You want to invest some money in a domest...
 11.5.22: Which Stock? You want to invest in a stock and have narrowed your c...
 11.5.23: In 2328, for each study, explain which statistical procedure (estim...
 11.5.24: In 2328, for each study, explain which statistical procedure (estim...
 11.5.25: In 2328, for each study, explain which statistical procedure (estim...
 11.5.26: In 2328, for each study, explain which statistical procedure (estim...
 11.5.27: In 2328, for each study, explain which statistical procedure (estim...
 11.5.28: In 2328, for each study, explain which statistical procedure (estim...
Solutions for Chapter 11.5: PUTTING IT TOGETHER: WHICH METHOD DO I USE?
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 11.5: PUTTING IT TOGETHER: WHICH METHOD DO I USE?
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. Chapter 11.5: PUTTING IT TOGETHER: WHICH METHOD DO I USE? includes 28 full stepbystep solutions. Since 28 problems in chapter 11.5: PUTTING IT TOGETHER: WHICH METHOD DO I USE? have been answered, more than 145082 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4.

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

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Bayesâ€™ 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

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

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 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

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.

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Contrast
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.

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

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.

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

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

Error mean square
The error sum of squares divided by its number of degrees of freedom.

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

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model

Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.