ECON 103 Lecture Notes - Causal Model, Null Hypothesis, Alternative Hypothesis

• School: UCLA
• Department: Economics
• Course: ECON 103
• Professor: rojas

Document Summary

This is a causal model because it is showing the cause and e ect relationship between the variables rather than predicting what salary one will have with a certain gpa and whether or not they took econometrics. The change in one variable is correlated to a change in another variable b) df=data. frame(x=c(0,4), y=c(0,100)) plot(df, df, xlab="gpa", ylab="sal") abline(a=10, b=5, col="blue") abline(a=30, b=5, col="red") legend(1, 95, legend=c("metrics=0", "metrics=1"), col=c("blue", "red"), lty=1:2, cex=0. 8) Sal = 1 + 3 + 1 + 2gp a d) Null hypothesis: 3 = 0, 2 = 0 alternative hypothesis: 3 6= 0, 2 6= 0 you have to gure out the f-stat. When all other variables are 0, missed has an intercept of -0. 358. When the interest rate goes up by 1, the. When the dollar value of mortgage goes up by 100,000, the missed variable increases by 0. 0732. If the mortgage has an adjustable rate, missed increases by 0. 0834.