- Chapter 1: What Is Statistics?
- Chapter 10: One-Sample Tests of Hypothesis
- Chapter 11: Two-Sample Tests of Hypothesis
- Chapter 12: Analysis of Variance
- Chapter 13: Correlation and Linear Regression
- Chapter 14: Multiple Regression Analysis
- Chapter 15: Index Numbers
- Chapter 16: Time Series and Forecasting
- Chapter 17: Nonparametric Methods: Goodness-of-Fit Tests
- Chapter 18: Nonparametric Methods: Analysis of Ranked Data
- Chapter 19: Statistical Process Control and Quality Management
- Chapter 2: Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation
- Chapter 20: An Introduction to Decision Theory
- Chapter 3: Describing Data: Numerical Measures
- Chapter 4: Describing Data: Displaying and Exploring Data
- Chapter 5: A Survey of Probability Concepts
- Chapter 6: Discrete Probability Distributions
- Chapter 7: Continuous Probability Distributions
- Chapter 8: Sampling Methods and the Central Limit Theorem
- Chapter 9: Estimation and Confidence Intervals
Statistical Techniques in Business and Economics 15th Edition - Solutions by Chapter
Full solutions for Statistical Techniques in Business and Economics | 15th Edition
Statistical Techniques in Business and Economics | 15th Edition - Solutions by ChapterGet Full Solutions
a-error (or a-risk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study
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.
Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability
Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.
The joint probability distribution of two random variables.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.
The mean of the conditional probability distribution of a random variable.
A probability distribution for a continuous random variable.
Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.
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).
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.
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.
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment
Another name for a cumulative distribution function.
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.
Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.
A function used in the probability density function of a gamma random variable that can be considered to extend factorials
In multiple regression, the matrix H XXX X = ( ) ? ? -1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .