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# Temporal Precedence And Assumptions of Regression Analysis

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# Temporal Precedence And Assumptions of Regression Analysis

HRA Presentation on Temporal Presence and Regression Analysis Assumptions MBA 3rd Sem

HRA Presentation on Temporal Presence and Regression Analysis Assumptions MBA 3rd Sem

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### Temporal Precedence And Assumptions of Regression Analysis

1. 1. TEMPORAL PRECEDENCE AND ASSUMPTIONS OF REGRESSION ANALYSIS
2. 2. TEMPORAL PRECEDENCE Meaning:- Temporal precedence Is the primary determinant used in answering a “CAUSE AND EFFECT” question. A question that requires a knowledge of what happened first in a event.
3. 3. ASSUMPTIONS OF REGRESSION ANALYSIS Meaning of Regression Analysis:- It is a statistical tool used to calculate a continuous dependent variable from various independent variables and it commonly used for prediction and forecasting.
4. 4. 1) There exists a linear relationship between independent variable(x)and dependent variable (y). The general linear regression equation y= a + bx+c is used to describe the relationship between the variables x and y. Here constant c shows the deviation of specific value of y and its desired value for a given value of x. 2) There exists an expected value of variable y and these are normally distributed, for each value of variable x. The expected value of normally distributed values will be located on the regression line. 3) The values of variable x are fixed (not be random) while the values of variable y is a continuous random variable.
5. 5. 1) It is assumed that sampling error associated with mean values of y, be an independent random variable and distributed normally with mean constant standard deviation and zero. 2) For every value of x lying within the sample data range, the standard deviation and variance of expected values of y about the regression line are constant. 3) The value of the y cannot be determined for the value of x (which is outside the boundary of the sample data).