Highlights
R Value interpretation if the value of R is near to 1 it shows a very strong relation between the two variables.
In this case the R value is very near to one this means that if infosys spends more on employee benefits then it will be able to fetch more sales.
R square is a statistical measure in a regression model that determines the proportion of variance in the dependant variable that can be explained by the independent variable. Thus, here in this case as the value of R square is high it is near to 1 showing that the two variables are quite dependant on each other.
| StatisticsMultiple | R0.64759476 |
| Square | 0.419378985 |
| Adjusted R Square | 0.346801358 |
| Standard Error | 6060.954418 |
| Observations | 10 |
Interpretation of the P-value
Coefficient of EBE(beta) - The sign of the coefficient determines whether there is a positive or a negative relation between the dependant and independent variable and in this case it is positive so the correlation is also positive that means that if infoysys spends on EBE the total assets will be 28.85 times or else it will only be 3811 and with EBE expenses it will be 28.85 times.
Intercept(alpha)- The sign of the coefficient determines whether there is a positive or a negative relation between the dependant and independent variable and in this case it is positive.
P-value greater than 0.05 is statistically insignificant and indicates strong evidence for null hypothesis but in this case the P-value is less than 0.05,then we can reject the null hypothesis .Hence, we can safely say that the hypothesis is true and total asset can be explained by employee benefit expenses is true.
It means that even if we spend 0 on the dependant variable the amount of independent variable will be 3811 in this case if we spend 0 on EBE still infosys will make total assets equal to 3811.
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