×
Log in to StudySoup

Forgot password? Reset password here

> > The Practice of Statistics 4

The Practice of Statistics 4th Edition - Solutions by Chapter

The Practice of Statistics | 4th Edition | ISBN: 9781429245593 | Authors: Daren S. Starnes; Dan Yates; David S. Moore

Full solutions for The Practice of Statistics | 4th Edition

ISBN: 9781429245593

The Practice of Statistics | 4th Edition | ISBN: 9781429245593 | Authors: Daren S. Starnes; Dan Yates; David S. Moore

The Practice of Statistics | 4th Edition - Solutions by Chapter

Solutions by Chapter
4 5 0 353 Reviews

Since problems from 12 chapters in The Practice of Statistics have been answered, more than 4801 students have viewed full step-by-step answer. The full step-by-step solution to problem in The Practice of Statistics were answered by , our top Statistics solution expert on 09/04/17, 10:29PM. The Practice of Statistics was written by and is associated to the ISBN: 9781429245593. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 4. This expansive textbook survival guide covers the following chapters: 12.

Key Statistics Terms and definitions covered in this textbook
  • 2 k p - factorial experiment

    A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

  • Acceptance region

    In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

  • Adjusted R 2

    A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • Backward elimination

    A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

  • Bias

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

  • C chart

    An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

  • Completely randomized design (or experiment)

    A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

  • Conditional probability mass function

    The probability mass function of the conditional probability distribution of a discrete random variable.

  • Contour plot

    A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

  • Cumulative distribution function

    For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

  • Curvilinear regression

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

  • Defects-per-unit 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.

  • Discrete distribution

    A probability distribution for a discrete random variable

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • Error mean square

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

  • 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 model-itting process and not on replication.

  • 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

  • Geometric random variable

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

×
Log in to StudySoup
Get Full Access to Thousands of Study Materials at Your School

Forgot password? Reset password here

Join StudySoup for FREE
Get Full Access to Thousands of Study Materials at Your School
Join with Email
Already have an account? Login here
Reset your password

I don't want to reset my password

Need an Account? Is not associated with an account
Sign up
We're here to help

Having trouble accessing your account? Let us help you, contact support at +1(510) 944-1054 or support@studysoup.com

Got it, thanks!
Password Reset Request Sent An email has been sent to the email address associated to your account. Follow the link in the email to reset your password. If you're having trouble finding our email please check your spam folder
Got it, thanks!
Already have an Account? Is already in use
Log in
Incorrect Password The password used to log in with this account is incorrect
Try Again

Forgot password? Reset it here