Regression Analysis Is the Technique Term Paper

Pages: 2 (567 words)  ·  Bibliography Sources: 3  ·  File: .docx  ·  Level: Master's  ·  Topic: Education - Mathematics

Regression analysis is the technique used to express the linear relationship between two variables. With this technique we can estimate the value of the dependent variable (Y) based on a selected value of the independent variable (X). This kind of analysis is mostly used to determine if sales numbers of a product a are related to the number of TV advertisements for that particular product during a specific timeframe. The mathematical equation for the line used to estimate the value of variable Y on the basis of variable X is also known as the regression equation (general form of linear regression equation: Y1 = a + bX) (Lind, Marchal, & Wathen, 2005).

Y1

= read Y prime, is the predicted value of Y for a selected X value a = is the Y-intercept, or the estimated value of Y when X = 0

b

= is the slope of the line, or the average change in Y1

X

= any value of the independent variable that is selected

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Linear regression is used to make predictions about a single variables value. In other words, it is used for discovering the equation for a line that most closely fits the given data (Lind, Marchal, & Wathen, 2005). That linear equation is then used to predict values for the data. For example: A sales manager wants to know if more sales calls will sell more copy machines, and by how much the number of calls have to increase to reach a certain number of sales for those machines. The main components are the slope and the intercept, also the standard errors and confidence intervals. Furthermore the correlation coefficient, and standard deviation are components of the linear regression analysis.

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