Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

November 11, 2023


Pages


DOI

Article

A study of the relationship between parents’ educational behavior and children’s psychological development based on linear regression models


Authors

Xuan Yao Affiliation:
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
and Jing Li Affiliation:
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.


Abstract

The purpose of this paper is to investigate the linear relationship between parenting and children’s psychological development and to analyze the strength of the relationship between them by using linear regression models. A one-dimensional nonparametric regression model with matrices is employed to handle the linear relationship between parenting and children’s psychological development. Combining parameter estimation and great-likelihood estimation was used to determine the maximum parameter value for the sample relationship. To ensure that the parameters that affect parenting and children’s mental health development conform to the model, we used the expectation and variance of the parameter estimates. The results show that good and bad parenting behavior affects children’s mental health. Benign parenting has a contributing effect on children’s emotional influence; children’s perception of safety is 0.75, and more stable emotions and stability are 0.85. When children are well educated, children’s three perceptions are 0.65, and self-perception is 0.8.


Keywords

Linear regression model, Parameter estimation, Great likelihood, Child psychology, Parenting behavior, 97B60


Citation

Yao, X. & Li, J. (2023). A study of the relationship between parents’ educational behavior and children’s psychological development based on linear regression models. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01111

Published by: Engineering Journals

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