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Property Values of Residential Areas - Biblical Point of View

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                                                                                        Kariem Herrarte

                                                                                    BUS STAT        

                                                                                    Feb 25, 19

Case study

When trying to find out the research questions and using the data set we can find out that with the data set we are able to identify multiple factors. Such as structural, environment, and economic factors that are able to affect the property values of residential areas.

        When trying to find out what variables are significant and which are not, we can find out the variable can come out as expected. When trying to find the regression equation we can use this p= -106692+0.209land- 706 age+ 2292time-56pop+69.2 gr+846087patio+56sedi+0.910imp. Which also allows us to see that the significant variables of gr and imp create p value of more than 0.5 level.

        The water quality creates a huge difference in pricing on houses. The lake is a huge attraction to why people want to be a part of the community. When the lakes quality is poor people do not want to live around it. Which can lower the population of homes in that community and lowers pricing because they want anyone to be apart of it bringing less revenue to them.

There are different types of variables such as the price dependent variable, as well as all independent variables all using the linear regression model. Another variable can be the economic variables such as land, time, pop, and lmp. The structural variables would be Gr, and patio. Lastly, the environment variable is sedi.

        When talking about variables and if they are statistically significant we can expect their outcomes to be multiple different ones. We can first check if the linear regression fits along with the two structural variables known as Gr which is significant and while patio is not. The regression output of Gr contains a p-value less than .5. Which allows us to see that the price in residency property can increase and will increase.

        In order to explain the impact of the population density when looking at housing we have to see the regression output. We are able to do that be finding out what can impact the housing prices, such as the population destiny. The variable that does this is pop, which is negative. We can also see that pop variable creates a downgrade coefficient at negative 56 percent. Which is not good because if housing goes down, then the population goes down, which also works both ways. Although, each time that the population goes up with by each person than the housing price goes down by 56 dollars.

        Lastly, we are asked to talk about how we suggest property developers, house buyers and local governments ways to improve their environment and economical community. We can also conclude that all factors such as structural, environmental and econ are constant. There are many ways to help improve the quality needed for communities. One way is by having the local decision makers lowering the amount of sedimentation that can impact house prices because of the amount of sedimentation in the lakes. If the lakes continue to get worse then people will not want to live in those communities, people leave then the population in that area goes down and the prices of housing will go up. The value of a house can also rise from how new it and the location of it. Closer and newer to the lake allows the prices to be higher and provide more revenue for each property and vice versa for the lower lots, with another idea being that they also increase the lot, sq ft of the house and lands. Which can create more value for each house and bring in more population to the communities. In conclusion in order to preform and have maximum profits, the lake must be clean and the homes most be top tier. By doing all of the things I suggested above it allows for more people to be interested in the communities.



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