BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -The whole time accounts for the variability outcomes, whatever ability in the dependent variable variable. That cannot be explained by the linear relationship, by the linear relationship you turned the variables.

Detailed explanation-2: -Within a linear regression model tracking a stock’s price over time, the error term is the difference between the expected price at a particular time and the price that was actually observed.

Detailed explanation-3: -In regression analysis, the dependent variable is denoted Y and the independent variable is denoted X. So, in this case, Y=total cholesterol and X=BMI. When there is a single continuous dependent variable and a single independent variable, the analysis is called a simple linear regression analysis .

Detailed explanation-4: -Simple linear regression is used to model the relationship between two continuous variables. Often, the objective is to predict the value of an output variable (or response) based on the value of an input (or predictor) variable.

Detailed explanation-5: -Error Term Defined y = b0 + bx + . In this equation, y is the dependent variable, x is the independent variable, b is the slope of a regression line, and b0 is the line’s intercept on the y-axis.