Managerial economics project
Statistical Significance of Parameter estimates (Airline data example)
The p-values associated with the calculated t-values give the exact level of significance at which the independent variable has a statistical significant effect on the dependent variable
(ρ) x 100
For instance, for the Price variable:
ρ = 0.00004, then
( 0.00004 ) * 100 = 0.004% level of significance
This means that there is only a 0.004% chance that the price per coach seat does not affect the sales of coach seats per flight
or (1 – 0.00004) x 100 = 99.996% level of confidence
At the 99.996% confidence level the price per coach seat affects the sales of coach seats per flight.
For the competitor’s price:
Ρ = 0.04664
Then (ρ) x 100 = (.04664) x 100 = 4.664%
there is only a 4.664% chance that the competitor’s price per coach seat does not affect the sales of seats per flight.
Or (1 – ρ) x 100 = (1 – .04664) x 100 = 95.336%
at the 95.336% confidence level the competitor’s price per seat affects the sales of coach seats per flight
For Income:
Ρ = 0.00931
Then (ρ) x 100 = (0.00931) x 100 = 0.931%
there is only a 0.931% chance that income does not affect the sales of seats per flight.
Or (1 – ρ) x 100 = (1 – .00931) x 100 = 99.069%
at the 99.069% confidence level income affects the sales of coach seats per flight
