#homoscedasticity

[insidemyvisualmind]

Hot as a volcán @homoscedasticity

[insidemyvisualmind]

[insidemyvisualmind]

My everyday man crush

[crunchiegranola]

Since I'm currently wrapping up my final undergrad year and writing my honour's thesis, I've been coming across some fancy new words that I just really like. Here's a couple of them:

~Autochthonous~ meaning something that comes from that original place rather than descended or migrated from somewhere else;

And

~Homoscedasticity~ meaning the data I'm processing has homogeneity of variance

...they're just so fun to say/write

[ijtsrd]

Comparative Analysis of Heteroscedastic and Homoscedastic OLS Models

by AkpensuenShiaondo Henry | Joel Simon | Alhaji Abdullahi Gwani | Joshua Hassan Jemna "Comparative Analysis of Heteroscedastic and Homoscedastic OLS Models"

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020,

URL: https://www.ijtsrd.com/papers/ijtsrd33553.pdf

Paper Url: https://www.ijtsrd.com/mathemetics/other/33553/comparative-analysis-of-heteroscedastic-and-homoscedastic-ols-models/akpensuenshiaondo-henry

callforpaperbiologicalscience, biologicalsciencejournal

This study considered foreign direct investment FDI as response variable while, gross domestic product GDP , inflation and exchange rate were the predictor variables. The data were obtained from the Central Bank of Nigeria Statistical Bulletin spanning from 1970 to 2019. The study aimed at comparing heteroscedatic and homoscedastic OLS modes. Our findings revealed that the predictor variables in the heteroscedastic OLS model were not significant and were able to account for about 44 of the variation in the response variable. The diagnosis of the fitted regression model using BreuschPagan test showed that the assumption of homoscedasticity was violated. To address the problem of heteroscedasticity, all the variables were converted to log form to stabilise the variance. Our results from the now homoscedstic model revealed that all the predictor variables were significant and able to account for about 82 of the variation in the response variable. Therefore, our study established that when the assumption of homoscedasticity is violated, the model parameters become inefficient, the standard errors biased and the t statistics and the p values no more valid. On the other hand, this study evidently proved that homoscedastic OLS model provide better estimates than heteroscedastic OLS model. 

[datasciencecity]

Assumptions of Linear Regression

Linear regression is an analysis that analyze whether one or more predictor variables explain the dependent variable. there are few assumption that we need to keep in mind to maintain accuracy of the regression model. Below are Basic Assumption of Regression Model:

Linear relationship

No or little multicollinearity

No auto-correlation

Homoscedasticity

1. Linear relationship

According to this…

View On WordPress

[biomedres]

Some Results on a Wilcoxon Mann-Whitney Approach to Interactions in a Two-Way ANOVA Design

Some Results on a Wilcoxon Mann-Whitney Approach to Interactions in a Two-Way ANOVA Design by Rand Wilcox in Biomedical Journal of Scientific & Technical Research (BJSTR) https://biomedres.us/fulltexts/BJSTR.MS.ID.000293.php