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    Linear Regression

    Linear regression is an approach to model the relationship between a scalar dependent variable y and one or more explanatory variable denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, it is called multiple linear regressions. In linear regression, data is modeled using linear predictor functions, and unknown model parameters are estimated from the data. Such models are called linear models.

    Linear regression was the first type of regression analysis to be studied rigorously, and to be used extensively in practical applications. This is due to the fact models depend linearly on their unknown parameters are easier to fit than models which are non-linearly related to their parameters; also because the statistical properties of the resulting estimators are easier to determine.

    Standard linear regression models with standard estimation techniques make a number of assumptions about the predictor variables, the response variables and their relationships. Numerous extensions have been developed that allow each of these assumptions to be relaxed and sometimes entirely eliminated. Numerous extensions of linear regression have been developed, which allow some or all of the assumptions underlying the basic model to be relaxed.  

    A large number of procedures have been developed for parameter estimation and inference in linear regression. These methods differ in computational simplicity of algorithms, presence of a closed-form solution, robustness with respect to heavy-tailed distributions, and theoretical assumptions needed to validate desirable statistical properties such as consistency and asymptotic efficiency.

    Linear regression has many application including biological, behavioral and social sciences. It is used to describe possible relationships between variables. Its ranked as one of the most important tools used in these disciplines. 

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    BrainMass Categories within Linear Regression

    Simple Linear Regression

    Solutions: 30

    Simple linear regression is the least squares estimator of a linear regression model with a single explanatory variable.

    Ordinary Least Squares

    Solutions: 13

    Ordinary least squares is a method for estimating the unknown parameters in a linear regression model.

    General Linear Model

    Solutions: 25

    The generalized linear model is a flexible generalization of ordinary linear regression that allows for response variables that have other than a normal distribution.

    Bayesian Regression

    Solutions: 0

    Bayesian linear regression is an approach in which the statistical analysis is undertaken within the context of Bayesian inference.

    BrainMass Solutions Available for Instant Download

    Linear Regression Analysis Prediction

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    Multiple Regression Analysis

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    Run a Multiple Linear Regression

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    linear regression and chi sq

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    steps on performing simple regression

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    Regression Analysis: Songs

    IPods (or iPod Apps on iPhones/iPod's) are incredibly popular for listening to music on the go. The music that you keep on an iPod can be stored in several different formats. Two popular formats are AIFF (Audio Interchange File Format) and AAC (Advanced Audio Coding). Files on an iPod can be in either of these formats, or both.

    Linear and Exponential Relation

    If a company took 100 hours to assemble their first unit and 85 hours to assemble the second unit, we might expect it to take: 70 hours to assemble the third unit. 72.25 hours to assemble the fourth unit. 72.25 hours to assemble the third unit. 70 hours to assemble the fourth unit.

    Correlation and Simple Linear Regression Using SPSS

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    Descriptive Statistics, Bivariate Analysis, and Linear Regressions

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    Regression Model Vs. Computerized Regression Routine

    What are the advantages and disadvantages of regression models in comparison to using a computerized regression routine? Give examples. What types of economic relations do managers take an interest in? Give examples and explain why they are interesting to managers.

    Regression Model for The Undrained Strength of Some Thawed Permafrost Soils

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    Hypothesis Testing and Linear Regression Analysis

    Please assist answering the below statistical analysis questions: 1) Explain the difference between the null and alternative hypothesis. Which one can be proven in a statistical sense? 2) Explain why it is always necessary to specify a fixed null value in the one-sample hypothesis test, while such specifications are generall

    Statistics Problem Set: Regression and Linear Programming

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    Linear Regression and Square Residuals

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    Solve: Line of Best Fit

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    Simple Linear Regression Test

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    Weinberger's problem using LP

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    Conducting a linear regression analysis

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    Forecasting: Develop a Linear Regression Model

    Apperson and Fitz is a chain of clothing stores that caters to high school and college students. It publishes a quarterly catalog and operates a Web site that features provocatively attired males and females. The Web site is very expensive to maintain, and company executives are not sure whether the number of hits at the site re

    Application of Linear Regression

    The management of a chain of fast food restaurants wants to investigate the relationship between the daily sales volume (in dollars) of a company restaurant and the number of competitor restaurants within a 1 mile radius. The following data have been collected: Number of competitors within 1 mile Sales 1 3600 1 3300 2 3100

    Cost Accounting: Favata, Trustme Vehicle, Konrade's Engine, Merriamn Company

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    Adriana Corporation Method of estimating costs: Simple Regression

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    Discuss: Statistical Variation and Regression Methods

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    Linear Regression of Monthly Electrical Usage

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    Data Analysis on Soft Drink Study

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    Linear Programming Problem for Print Media Advertising (PMA)

    Print Media Advertising (PMA) has been given a contract to market Buzz Cola via newspaper ads in a major southern newspaper. Full-page ads in the weekday editions (Monday through Saturday) cost $2000, whereas on Sunday a full-page ad costs $8000. Daily circulation of newspaper is 30,000 on weekdays and 80,000 on Sundays. PMA