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

1. TEMPORAL PRECEDENCE
AND ASSUMPTIONS OF
REGRESSION ANALYSIS

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. 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. 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. 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).