{"id":53524,"date":"2024-04-15T23:55:14","date_gmt":"2024-04-15T23:55:14","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=53524"},"modified":"2024-04-15T23:55:14","modified_gmt":"2024-04-15T23:55:14","slug":"an-estimation-of-relationship-between-one-independent-variable-and-dependent-variable-is-known-as","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/an-estimation-of-relationship-between-one-independent-variable-and-dependent-variable-is-known-as\/","title":{"rendered":"An estimation of relationship between one independent variable and dependent variable is known as"},"content":{"rendered":"

[amp_mcq option1=”simple regression” option2=”Two way regression” option3=”One variable series” option4=”multiple regression” correct=”option1″]<\/p>\n

The correct answer is A. simple regression.<\/p>\n

Simple regression is a statistical method that analyzes the relationship between one dependent variable and one independent variable. The dependent variable is the variable that is being predicted, and the independent variable is the variable that is being used to make the prediction.<\/p>\n

Simple regression is a linear model, which means that it assumes that the relationship between the dependent and independent variables is linear. This means that the change in the dependent variable is proportional to the change in the independent variable.<\/p>\n

Simple regression is a powerful tool that can be used to make predictions about the dependent variable. However, it is important to note that simple regression can only be used to make predictions when the relationship between the dependent and independent variables is linear. If the relationship is not linear, then simple regression will not be able to make accurate predictions.<\/p>\n

Here is a brief explanation of each option:<\/p>\n