Forecasting Academic Performance using Multiple Linear Regression

Aung Cho; Yee Mon Khaing

Title:
Forecasting Academic Performance using Multiple Linear Regression

Authors:
Yee Mon Khaing | Aung Cho

Cite This Article :

Yee Mon Khaing | Aung Cho "Forecasting Academic Performance using Multiple Linear Regression" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5, August 2019, pp.1187-1189, URL: https://www.ijtsrd.com/papers/ijtsrd26517.pdf

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Abstract :
Regression is one of the most powerful statistical methods used in educational researches. This paper shows the important instance of regression methodology called Multiple Linear Regression (MLR) and proposes a framework of the forecasting of the students’ test scores, based on Intelligence Quotient (IQ) and the number of hours that the students studied. This paper was applied the aid of the Statistical Package for Social Sciences (SPSS) version 23 and PYTHON version 3.7.

Keywords :
Multiple Linear Regressions (MLR), Statistical Package for Social Sciences (SPSS)

Publication Details:

Unique Identification Number : IJTSRD26517

Published In : Volume-3 | Issue-5, August 2019

Page Number(s) : 1187-1189

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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