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Let's break down the steps for solving this regression problem:

Given data:

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Elevation (feet)	7000	4000	6000	3000	7000	4500	5000
Temperature (°F)	50	60	48	70	55	55	60

Elevation (in feet	7000	4000	6000	3000	7000	4500	5000
Temperature (0F)	50	60	48	70	55	55	60

 

(i) Find a regression equation for elevation and city temperature on a given day.

(ii) Find the residuals and create a residual plot.

(iii) Use the regression equation to estimate the city temperature for the city situated at an elevation of 5500ft.

(iv) Find the correlation coefficient and coefficient of determination and interpret both.

What is meant by the problem of identification? Explain the conditions for identification.

What do you mean by the term ‘Logs’ in the context of economic data? Give an account of the factors contributing to ‘Log effect’. Give illustration in support of your answer

Discuss the difference between Univariate, Bivariate and Multivariate analysis?

Distinguish between Logit model and Probit model. Explain with illustration the process involved in estimation of Logit model.

A standard error of the estimate is a measure of the accuracy of predictions. Elucidate.

What is the difference between random effects approach and fixed effects approach for estimation of parameters? State the assumptions of fixed effects model.