 Chapter Chapter 1: What Is Statistics?
 Chapter Chapter 10: OneSample Tests of Hypothesis
 Chapter Chapter 11: TwoSample Tests of Hypothesis
 Chapter Chapter 12: Analysis of Variance
 Chapter Chapter 13: Correlation and Linear Regression
 Chapter Chapter 14: Multiple Regression Analysis
 Chapter Chapter 15: Index Numbers
 Chapter Chapter 16: Time Series and Forecasting
 Chapter Chapter 17: Nonparametric Methods: GoodnessofFit Tests
 Chapter Chapter 18: Nonparametric Methods: Analysis of Ranked Data
 Chapter Chapter 19: Statistical Process Control and Quality Management
 Chapter Chapter 2: Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation
 Chapter Chapter 20: An Introduction to Decision Theory
 Chapter Chapter 3: Describing Data: Numerical Measures
 Chapter Chapter 4: Describing Data: Displaying and Exploring Data
 Chapter Chapter 5: A Survey of Probability Concepts
 Chapter Chapter 6: Discrete Probability Distributions
 Chapter Chapter 7: Continuous Probability Distributions
 Chapter Chapter 8: Sampling Methods and the Central Limit Theorem
 Chapter 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
ISBN: 9780073401805
Statistical Techniques in Business and Economics  15th Edition  Solutions by Chapter
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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.

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

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

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

Box plot (or box and whisker plot)
A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

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

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

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.

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

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 random variable
A random variable with a inite (or countably ininite) range.

Distribution free method(s)
Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

Error of estimation
The difference between an estimated value and the true value.

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.

Event
A subset of a sample space.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

Fraction defective control chart
See P chart

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 mean.
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .