- 12.12.1: Whats wrong? For each of the following, explain what is wrong and w...
- 12.12.2: Whats wrong? For each of the following, explain what is wrong and w...
- 12.12.3: Computing the pooled standard deviation. An experiment was run to c...
- 12.12.4: Visualizing the ANOVA model. For each of the following situations, ...
- 12.12.5: Whats wrong? For each of the following, explain what is wrong and w...
- 12.12.6: Determining the critical value of F. For each of the following situ...
- 12.12.7: Why no multiple comparisons? Any pooled two-sample t problem can be...
- 12.12.8: Growth of Douglas fir seedlings. An experiment was conducted to com...
- 12.12.9: A one-way ANOVA example. A study compared 4 groups with 6 observati...
- 12.12.10: Calculating the ANOVA F test P-value. For each of the following sit...
- 12.12.11: Calculating the ANOVA F test P-value, continued. For each of the fo...
- 12.12.12: Calculating the pooled standard deviation. An experiment was run to...
- 12.12.13: Describing the ANOVA model. For each of the following situations, i...
- 12.12.14: Describing the ANOVA model, continued. For each of the following si...
- 12.12.15: Determining the degrees of freedom. Refer to Exercise 12.13. For ea...
- 12.12.16: Determining the degrees of freedom, continued. Refer to Exercise 12...
- 12.12.17: Data collection and the interpretation of results. Refer to Exercis...
- 12.12.18: Data collection, continued. Refer to Exercise 12.14. For each situa...
- 12.12.19: Pain tolerance among sports teams. Many have argued that sports suc...
- 12.12.20: Multitasking with technology in the classroom. Laptops and other di...
- 12.12.21: Contrasts for multitasking. Refer to the previous exercise. Let m1,...
- 12.12.22: Residual analysis. In this chapter, we considered comparing sample ...
- 12.12.23: Organic foods and morals? Organic foods are often marketed using mo...
- 12.12.24: Organic foods and morals, continued. Refer to the previous exercise...
- 12.12.25: Organic foods and friendly behavior? Refer to Exercise 12.23 for th...
- 12.12.26: Massage therapy for osteoarthritis of the knee. Various studies hav...
- 12.12.27: Shopping and bargaining in Mexico. Price haggling and other bargain...
- 12.12.28: The effect of increased variation within groups. The One-Way ANOVA ...
- 12.12.29: The effect of increased variation between groups. Set the pooled st...
- 12.12.30: The effect of increased sample size. Set the pooled standard error ...
- 12.12.31: Financial incentives for weight loss. The use of financial incentiv...
- 12.12.32: Financial incentives for weight loss, continued. Refer to the previ...
- 12.12.33: Changing the response variable. Refer to the previous two exercises...
- 12.12.34: Do labels matter? A study was performed to examine the self-identif...
- 12.12.35: The multiple-play strategy. Multiple play is a bundling strategy th...
- 12.12.36: The multiple-play strategy. Multiple play is a bundling strategy th...
- 12.12.37: Do we experience emotions differently? Do people from different cul...
- 12.12.38: The emotions study, continued. Refer to the previous exercise. The ...
- 12.12.39: The effects of two stimulant drugs. An experimenter was interested ...
- 12.12.40: Restaurant ambiance and consumer behavior. There have been numerous...
- 12.12.41: Writing contrasts. Return to the eye study described in Example 12....
- 12.12.42: Analyzing contrasts. Answer the following questions for the two con...
- 12.12.43: College dining facilities. University and college food service oper...
- 12.12.44: Animals on product labels? Recall Exercise 7.72 (page 469). This ex...
- 12.12.45: Do isoflavones increase bone mineral density? Kudzu is a plant that...
- 12.12.46: Do poets die young? According to William Butler Yeats, She is the G...
- 12.12.47: Exercise and healthy bones. Many studies have suggested that there ...
- 12.12.48: Exercise and healthy bones, continued. Refer to the previous exerci...
- 12.12.49: Two contrasts of interest for the stimulant study. Refer to Exercis...
- 12.12.50: Orthogonal polynomial contrasts. Recall the Facebook friends study....
- 12.12.51: were made of inert materials (MAT). There were three mice used per ...
- 12.12.52: A comparison of different types of scaffold material, continued. Re...
- 12.12.53: Contrasts for the massage study. Refer to Exercise 12.26 (page 681)...
- 12.12.54: A dandruff study. Analysis of variance methods are often used in cl...
- 12.12.55: The dandruff study, continued. Refer to the previous exercise. DAND...
- 12.12.56: Comparing each pair of dandruff treatments. Refer to Exercise 12.54...
- 12.12.57: Testing several contrasts from the dandruff study. Refer to Exercis...
- 12.12.58: Changing the response variable. Refer to Exercise 12.51 (page 687),...
- 12.12.59: More on changing the response variable. Refer to the previous exerc...
- 12.12.60: Linear transformation of the response variable. Refer to the previo...
- 12.12.61: Comparing three levels of reading comprehension instruction. A stud...
- 12.12.62: More on the reading comprehension study. In the study described in ...
- 12.12.63: More on the Facebook friends study. Refer to the Facebook friends s...
- 12.12.64: Overall standard deviation versus the pooled standard deviation. Th...
- 12.12.65: Search the Internet. Search the Internet or your library to find a ...
- 12.12.66: A power calculation exercise. In Example 12.26 (page 676) the power...
- 12.12.67: in Exercise 12.37 (page 684). Suppose that you are planning a new s...
- 12.12.68: Planning another isoflavone study. Exercise 12.45 (page 686) gave d...
- 12.12.69: Planning another restaurant ambiance study. Exercise 12.40 (page 68...
Solutions for Chapter 12: One-Way Analysis of Variance
Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card | 8th Edition
ISBN: 9781464158933
Since 69 problems in chapter 12: One-Way Analysis of Variance have been answered, more than 50583 students have viewed full step-by-step solutions from this chapter. Chapter 12: One-Way Analysis of Variance includes 69 full step-by-step solutions. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8. This expansive textbook survival guide covers the following chapters and their solutions. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933.
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2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.
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All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions
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Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average
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Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.
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Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
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Bayes’ estimator
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.
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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.
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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.
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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 .
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Counting techniques
Formulas used to determine the number of elements in sample spaces and events.
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Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
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Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.
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Defects-per-unit control chart
See U chart
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Discrete distribution
A probability distribution for a discrete random variable
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Discrete random variable
A random variable with a inite (or countably ininite) range.
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Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
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Event
A subset of a sample space.
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Fisher’s least signiicant difference (LSD) method
A series of pair-wise hypothesis tests of treatment means in an experiment to determine which means differ.
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Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.
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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