.pass_color_to_child_links a.u-inline.u-margin-left--xs.u-margin-right--sm.u-padding-left--xs.u-padding-right--xs.u-relative.u-absolute.u-absolute--center.u-width--100.u-flex-inline.u-flex-align-self--center.u-flex-justify--between.u-serif-font-main--regular.js-wf-loaded .u-serif-font-main--regular.amp-page .u-serif-font-main--regular.u-border-radius--ellipse.u-hover-bg--black-transparent.web_page .u-hover-bg--black-transparent:hover. Content Header .feed_item_answer_user.js-wf-loaded . In this article, we have used simple examples and SPSS and excel to illustrate linear regression analysis and encourage the readers to analyze their data by these techniques. Conflicts of interest There are no conflicts of interest.
R Square is the coefficient of determination which here means that 92% of the variation can be explained by the variables.
Adjusted R square adjusts for multiple variables and should be used here. [Table 7] shows how to create a linear regression equation from the data.
Regression analysis allows predicting the value of a dependent variable based on the value of at least one independent variable.