 6.1.1: Toss 4 times Suppose you toss a fair coin 4 times. Let X = the numb...
 6.1.2: Pairadice Suppose you roll a pair of fair, sixsided dice. Let T ...
 6.1.3: Spellchecking Spellchecking software catches nonword errors, whic...
 6.1.4: Kids and toys In an experiment on the behavior of young children, e...
 6.1.5: Benfords law Faked numbers in tax returns, invoices, or expense acc...
 6.1.6: Working out Choose a person aged 19 to 25 years at random and ask, ...
 6.1.7: Benfords law Refer to Exercise 5. The first digit of a randomly cho...
 6.1.8: Working out Refer to Exercise 6. Consider the events A = works out ...
 6.1.9: Keno Keno is a favorite game in casinos, and similar games are popu...
 6.1.10: Fire insurance Suppose a homeowner spends $300 for a home insurance...
 6.1.11: Spellchecking Refer to Exercise 3. Calculate the mean of the rando...
 6.1.12: Kids and toys Refer to Exercise 4. Calculate the mean of the random...
 6.1.13: Benfords law and fraud A notsoclever employee decided to fake his...
 6.1.14: Life insurance A life insurance company sells a term insurance poli...
 6.1.15: Spellchecking Refer to Exercise 3. Calculate and interpret the sta...
 6.1.16: Kids and toys Refer to Exercise 4. Calculate and interpret the stan...
 6.1.17: Benfords law and fraud Refer to Exercise 13. It might also be possi...
 6.1.18: Life insurance (a) It would be quite risky for you to insure the li...
 6.1.19: Housing in San Jose How do rented housing units differ from units o...
 6.1.20: Size of American households In government data, a household consist...
 6.1.21: Random numbers Let X be a number between 0 and 1 produced by a rand...
 6.1.22: Random numbers Let Y be a number between 0 and 1 produced by a rand...
 6.1.23: Running a mile A study of 12,000 ablebodied male students at the U...
 6.1.24: ITBS scores The Normal distribution with mean m = 6.8 and standard ...
 6.1.25: Ace! Professional tennis player Rafael Nadal hits the ball extremel...
 6.1.26: Pregnancy length The length of human pregnancies from conception to...
 6.1.27: Multiple choice: Select the best answer for Exercises 27 to 30. Exe...
 6.1.28: Multiple choice: Select the best answer for Exercises 27 to 30. Exe...
 6.1.29: Multiple choice: Select the best answer for Exercises 27 to 30. Exe...
 6.1.30: Multiple choice: Select the best answer for Exercises 27 to 30. Exe...
 6.1.31: Exercises 31 to 34 refer to the following setting. Many chess maste...
 6.1.32: Exercises 31 to 34 refer to the following setting. Many chess maste...
 6.1.33: Exercises 31 to 34 refer to the following setting. Many chess maste...
 6.1.34: Exercises 31 to 34 refer to the following setting. Many chess maste...
Solutions for Chapter 6.1: Discrete and Continuous Random Variables
Full solutions for The Practice of Statistics  5th Edition
ISBN: 9781464108730
Solutions for Chapter 6.1: Discrete and Continuous Random Variables
Get Full SolutionsSince 34 problems in chapter 6.1: Discrete and Continuous Random Variables have been answered, more than 6102 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 6.1: Discrete and Continuous Random Variables includes 34 full stepbystep solutions.

Bias
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

Bimodal distribution.
A distribution with two modes

Bivariate normal distribution
The joint distribution of two normal random variables

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

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 variance.
The variance of the conditional probability distribution of a random variable.

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

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 .

Correlation
In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

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

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

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

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.

Exponential random variable
A series of tests in which changes are made to the system under study

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

Fisherâ€™s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

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

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.