Question

ht: We would like to analyse expenditures on research and development and use regression analysis, that the total expenditures would be closely related to the income, GDP, investments and inflation rate. describe results and quality of regression model. inferences about the regression model parameters. Test usefulness of the model. Are parameters cally significant? Please set up correct hypothesis and formulate your conclusions. UMMARY OUTPUT 0,9499 Regression Statistics bultiple Square 0,9023 djusted R Square 0.8878 Standard Error 1294.9574 Observations ANOVA Significance F 3,058E-13 Regression Residual Total SS 4.180E+08 1,045E08 6,232E+01 4.528E+07 1.677E+06 4,633E+08 27 Intercept Coefficients - 1754,8285 3.0913 0,0719 0,8100 -24,6261 Standard Error 7818,3439 1.6497 0,4915 0,3471 37,5128 Star Star -0,2245 1.8738 0,1463 2,3337 -0,6565 Powalue 0,8241 0.0718 0,8848 0,0273 0,5171 Lower 9596 Upper 9596 -17796,7451 14287,0880 -0,29366 ,4762 -0,9367 1,0805 0,0978 1,5221 - 101,5960 52,3438 GDP Investments

Answer 1

Please don't hesitate to give a "thumbs up" for the answer in case the answer has helped you

Inferences:

The following inferences are to be made from the model:

R-square - is at 0.9023 or 90.23% which means 90.23% of the variation in the "total expenditure" are explained by the
variation in "Income", "GDP", "investments", and "inflation rate". It is a strong R-Square - which means that the model'
predictive power is high, and has almost all the variables to successfully explain the response variable - "total expenditure"

Predictor variables - At an overall level, the ANOVA table has a p-value of < .05, indicating at least 1 variable is statistically significant. and that the equation can be used to predict the response
variable

"Intercept"  If all other variables are 0 , then y^ = 0 + Intercept = -1754.8285. But since p-value is > .05 this variable is not statistically significant, indicating that actually Intercept = 0. This can be interpreted as "if Income, GDP, Investments and Inflation Rate are 0 then the total expenditure is 0"

"GDP" : has p-value > .05, which means it is not statistically significant.

"Income" is also not statistically significant, as p-value < .05

"Investments" has a p-value of < .05, which means that per increase in investment by $1, the total expenditure increases by $0.8100

"Inflation Rate" has a p-value of < .05, which means that per increase in inflation by 1 point, the total expenditure decreases by $24.6261, which makes sense , because if cost of goods increases due to inflation then total expenditures decreases.