 4.2.45: Learning biology with computers An educator wants to compare the ef...
 4.2.46: Cell phones and brain cancer One study of cell phones and the risk ...
 4.2.47: Chocolate and happy babies A University of Helsinki (Finland) study...
 4.2.48: Child care and aggression A study of child care enrolled 1364 infan...
 4.2.49: Effects of class size Do smaller classes in elementary school reall...
 4.2.50: Effects of binge drinking A common definition of binge drinking is ...
 4.2.51: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.52: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.53: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.54: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.55: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.56: For the experiments described in Exercises 51 to 56, identify the e...
 4.2.57: Cocoa and blood flow A study conducted by Norman Hollenberg, profes...
 4.2.58: Reducing unemployment Will cash bonuses speed the return to work of...
 4.2.59: Layoffs and survivor guilt Workers who survive a layoff of other em...
 4.2.60: Effects of TV advertising Figure 4.2 (page 239) displays the 6 trea...
 4.2.61: Stronger players A football coach hears that a new exercise program...
 4.2.62: Killing weeds A biologist would like to determine which of two bran...
 4.2.63: Do diets work? Dr. Linda Stern and her colleagues recruited 132 obe...
 4.2.64: The effects of day care Does day care help lowincome children stay...
 4.2.65: Headache relief Doctors identify chronic tensiontype headaches as h...
 4.2.66: More rain for California? The changing climate will probably bring ...
 4.2.67: Treating prostate disease A large study used records from Canadas n...
 4.2.68: Getting teachers to come to school Elementary schools in rural Indi...
 4.2.69: Do placebos really work? Researchers in Japan conducted an experime...
 4.2.70: Pain relief study Fizz Laboratories, a pharmaceutical company, has ...
 4.2.71: Meditation for anxiety An experiment that claimed to show that medi...
 4.2.72: Testosterone for older men As men age, their testosterone levels gr...
 4.2.73: Do diets work? Refer to Exercise 63. Subjects in the lowcarb diet ...
 4.2.74: Acupuncture and pregnancy A study sought to determine whether the a...
 4.2.75: Doctors and nurses Nursepractitioners are nurses with advanced qua...
 4.2.76: Comparing cancer treatments The progress of a type of cancer differ...
 4.2.77: In the cornfield An agriculture researcher wants to compare the yie...
 4.2.78: Comparing weightloss treatments Twenty overweight females have agr...
 4.2.79: Aw, rats! A nutrition experimenter intends to compare the weight ga...
 4.2.80: Technology for teaching statistics The Brigham Young University (BY...
 4.2.81: Look, Ma, no hands! Does talking on a handsfree cell phone distrac...
 4.2.82: Chocolate gets my heart pumping Cardiologists at Athens Medical Sch...
 4.2.83: Room temperature and dexterity An expert on worker performance is i...
 4.2.84: Carbon dioxide and tree growth The concentration of carbon dioxide ...
 4.2.85: Got deodorant? A group of students wants to perform an experiment t...
 4.2.86: Close shave Which of two brands (X or Y) of electric razor shaves c...
 4.2.87: Multiple choice: Select the best answer for Exercises 87 to 94. Can...
 4.2.88: Multiple choice: Select the best answer for Exercises 87 to 94. In ...
 4.2.89: Multiple choice: Select the best answer for Exercises 87 to 94. To ...
 4.2.90: Multiple choice: Select the best answer for Exercises 87 to 94. A g...
 4.2.91: Multiple choice: Select the best answer for Exercises 87 to 94. Cor...
 4.2.92: Multiple choice: Select the best answer for Exercises 87 to 94. A r...
 4.2.93: Multiple choice: Select the best answer for Exercises 87 to 94. A f...
 4.2.94: Multiple choice: Select the best answer for Exercises 87 to 94. Two...
 4.2.95: Seed weights (2.2) Biological measurements on the same species ofte...
 4.2.96: Twins (1.3, 3.1) A researcher studied a group of identical twins wh...
Solutions for Chapter 4.2: Experiments
Full solutions for The Practice of Statistics  5th Edition
ISBN: 9781464108730
Solutions for Chapter 4.2: Experiments
Get Full SolutionsChapter 4.2: Experiments includes 52 full stepbystep solutions. Since 52 problems in chapter 4.2: Experiments have been answered, more than 6354 students have viewed full stepbystep solutions from this chapter. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. This expansive textbook survival guide covers the following chapters and their solutions.

`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

Alias
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

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

Chance cause
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

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

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Conidence interval
If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Defectsperunit control chart
See U chart

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.

Dependent variable
The response variable in regression or a designed experiment.

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 modelitting process and not on replication.

Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

Expected value
The expected value of a random variable X is its longterm average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

Extra sum of squares method
A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

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

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .