Hi, I just need to know what commands of Stata will I use to solve this question

Question

Hi, I just need to know what commands of Stata will I use to solve this question. We have a STATA file and that includes categories such as sqft, price, bedrooms, baths, age, owner, pool, traditional, fireplace, waterfront etc. And we have to use Stata commands to solve this question. Please help!

The file Br2.dta contains data on 1080 houses sold in Baton Rouge, Louisiana, during the mid-2005.The data include sale price, the house size in square feet, its age, whether it has a pool or fireplace or is on the waterfront. Also included is an indicator variable TRADITIONAL indicating whether the house style is traditional or not. 1- Plot house price against house size for houses with traditional style 2-For the traditional-style houses estimate the linear regression model PRICE = beta_1 + beta_2 SQFT + e Interpret the estimates. Compute elasticity of SQFT at means. Give an interpretation of your result Compute average of elasticity of SQFT. Give an interpretation of your result From your table of results, give a measure of var(b_2) and var (e). Deduce from your findings sigma (SQFT SQFT)^2. Draw a sketch of the fitted regression line. Compute the PRICE prediction of the model for a 4000 square foot house, both by hand and using STATA. Compute the least squared residuals and plot them against SQFT. Do any of our assumptions appear violated?

Explanation / Answer

you must use the regress command to fit the regression line

the command is as follows in your case

regress Price sqft

The variable immediatly after the regress command is output variable and rest of the variables are the input variables

to produce a scatter plot you must use

scatter price house

5 the regression plot is generated by default as a part of the regress command

you can use the predict command to predict the value of a new value

predict price_predict

6 to get the residual plot you must use the command after running the regression command

rvfplot, yline(0)

without the data only the above questions can be answered.

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