MGMT 1050 Chapter Notes - Chapter 16: Squared Deviations From The Mean, Regression Analysis, Dependent And Independent Variables
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Regression analysis: used to predict the values of one variable on the basis of another variable: require two factors, often two sets of interval data. Dependent variable: dependent on another variable (denoted as y) Independent variable: is not dependent on another variable (denoted as x) To determine whether a relationship exists, we employ a correlation analysis. After a regression analysis, need to develop a mathematical equation or model to accurately describe the nature of the relationship that exists between the dependent and independent variable. Probabilistic model: a method to represent the randomness that is a part of the real-life process. Error variable: the difference between the actual value and the estimated value. This formula helps determine line of best fit. To determine the relationship between x and y, we need to know the values of the coefficients. Least squares line: the best straight line, sum of deviations is the smallest.
