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Solutions for Chapter Chapter 23: Two Categorical Variables: The Chi-Square Test

Full solutions for The Basic Practice of Statistics | 4th Edition

ISBN: 9780716774785

Solutions for Chapter Chapter 23: Two Categorical Variables: The Chi-Square Test

Solutions for Chapter Chapter 23
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Textbook: The Basic Practice of Statistics
Edition: 4
Author: David S. Moore
ISBN: 9780716774785

This textbook survival guide was created for the textbook: The Basic Practice of Statistics, edition: 4. Since 48 problems in chapter Chapter 23: Two Categorical Variables: The Chi-Square Test have been answered, more than 7700 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter Chapter 23: Two Categorical Variables: The Chi-Square Test includes 48 full step-by-step solutions. The Basic Practice of Statistics was written by and is associated to the ISBN: 9780716774785.

Key Statistics Terms and definitions covered in this textbook
  • 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

  • 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

  • Bivariate normal distribution

    The joint distribution of two normal random variables

  • Conditional variance.

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

  • Contingency table.

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

  • Continuity correction.

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

  • Convolution

    A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

  • 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.

  • Correlation coeficient

    A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

  • Cumulative normal distribution function

    The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

  • Cumulative sum control chart (CUSUM)

    A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

  • Defect concentration diagram

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

  • Density function

    Another name for a probability density function

  • Discrete uniform random variable

    A discrete random variable with a inite range and constant probability mass function.

  • Dispersion

    The amount of variability exhibited by data

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • 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.

  • Experiment

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

  • Forward selection

    A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

  • 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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