Adjusted r-squared, Advanced Statistics

Assignment Help:

R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also establishes the percentage of data that is near to goodness of fit. 

S = 0.0903972   R-Sq = 26.3%   R-Sq(adj) = 26.1%

In this case R-squared is 26.3%; this indicates that there is a variation in Y (Wfood) in relation to the linear relationship between the Y and X variables.  The remaining percentage (73.7%) is the variation which is unknown.

The adjusted R-squared figure of 26.1% is a more accurate measure of the goodness of fit and as it is lower than r-squared and it indicates that certain explanatory variables are missing therefore the fluctuation of the dependent variable is not fully measured.


Related Discussions:- Adjusted r-squared

Finite population correction, This term sometimes used to describe the extr...

This term sometimes used to describe the extra factor in variance of the sample mean when n sample values are drawn without the replacement from the finite population of size N. Th

Command-line options, Command-Line options Compression: C++:  ./comp...

Command-Line options Compression: C++:  ./compress  -f  myfile.txt  [-o  myfile.hzip  -s Java:  sh  compress.sh  -f  myfile.txt  [-o  myfile.hzip  -s] Decompression:

Deviance, The measure of the degree to which the particular model differs f...

The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a

Zero sumgame, Zero sumgame is a game played by the number of persons in wh...

Zero sumgame is a game played by the number of persons in which the winner takes all stakes given by the losers so that the algebraic sum of gains at any stage is zero. Number of

Dummy variable, Discuss the use of dummy variables in both multiple linear ...

Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible

Explain kurtosis, Kurtosis: The extent to which the peak of the unimodal p...

Kurtosis: The extent to which the peak of the unimodal probability distribution or the frequency distribution departs from its shape of the normal distribution, by either being mo

Multi co linearity, Multi co linearity is the term used in the regression ...

Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the

Product-limit estimator, Product-limit estimator is a method for estimatin...

Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu

Marginal matching, Marginal matching is the matching of the treatment grou...

Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd