Data set for the tasks: https://drive.google.com/file/d/14hxIfvGvAaNqOBoq8cdwnKc864Q-X9Ey/view?usp=sharing

Please use STATA 14 or STATA 15 to do this.

Loxton is a small town with two suburbs.The data file "Data Set" contains data on 545 houses sold in Loxton between 2015 and 2020. This data includes the price at which the house was sold, which of two agents sold the house (all houses are sold through an agent by law), the year in which the house was sold as well as data on various characteristics of each house sold (age, size, number of stories etc.). These characteristics serve as possible explanatory variables of sale price.Data definitions follow:

OBS= observation

AGE= age of house in years

SHOPS= 1if house is close to shopping precinct, 0 otherwise

CRIME= crime rate of the suburb within which the house is located

TOWN= distance in kilometres to the town centre

STORIES= number of dwelling stories

OCEAN= 1 if house has an ocean view, 0 otherwise

POOL= 1 if house has a pool, 0 otherwise

PRICE= price at which the house was sold (in dollars)

SELLER=selling agent -"W&M"(0)or "A&B"(1)

SIZE=size of the house in square metres

SUBURB= Mayfair(0)or Claygate(1)

TENNIS= 1 if house has a tennis court, 0 otherwise

SOLD=year of last sale (2015 to 2020)

Your tasks:

Task 1. You are required to provide a comprehensive summary of the data set contained in the "Major Project -Data Set" file. However, it is recommended that you consider using both summary statistic and graphical methods while also noting any peculiarities within the data set.

Task 2(including Headline Regression Model). You have been hired by Jane, the wealthy owner of a house on Elm Street in Loxton(not included in the data set) to predict the price at which her house will sell. Her house has two stories, is in Claygate, is 192square metres large, is not near a shopping precinct and is 10 km from the town centre. She estimates that the house is about 10 years old and in a low crime area according to her experiences. Jane inherited the house from heruncle and is therefore unsure when it was last sold.Some other features of the property can be seen below:

Views of and from the house whose sale price you are to predict

\f