University Financial and Cost Analysis Homework Assignment

This assignment analyzes the financial implications of land slope on housing prices for a housing developer in Iowa. The student utilizes linear and multiple regression models to determine if the cost of grading uneven land is justified by potential increases in sale prices. The assignment includes regr...Read More

Running head: FINANCIAL AND COST ANALYSIS
Financial and Cost Analysis
Name of the student:
Name of the University:
Author note:

1
FINANCIAL AND COST ANALYSIS
Table of Contents
Answer to the question 1............................................................................................................2
Answer to the question 2............................................................................................................2
Answer to the question 3............................................................................................................4
Answer to the question 4............................................................................................................5
References and bibliography......................................................................................................6

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FINANCIAL AND COST ANALYSIS
Answer to the question 1
Table 1 simple linear Regression Output (model 1)
Procedure : (The table 1 shows the output of linear regression. This can be done with
the help of MS-Excel data analysis tool pack. To calculate this output you may go to
data + regression+ putting the dependent and independent variable + You may get the
solution. The first table shows the multiple R mean correlation, coefficient of
determination means R-squuare , standard error etc. The second tbale shows the
ANOVA table and the thid one is your coeffient and slope table. Here you get test
statistic, P- value and confidence interval.). The bibliography or references is depends
upon your assignment. If you put refeences then it is good.
The coefficient of land slope variable is 25527.65
The regression model is
Sale price= Intercept + slope of the land slope* land slope
Sale price = 179611.73 + 25527.65 * land slope

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FINANCIAL AND COST ANALYSIS
Yes. When a person pay more or less money for land then the land slope changes.
Thus this identify that price of a land depends upon the slope of the land.
Answer to the question 2
The regression model is
Sale price= Intercept + slope of the land slope* land slope
Sale price = 179611.73 + 25527.65 * land slope
To improve the liner regression analysis the first step is to fit many more models. In
this step firstly construct a simple model. That is to increase independent variables. After that
construct many regression model with several combination. The second way to improve the
regression analysis is take explanatory analysis. The explanatory analysis is an analysis
which gives a better regression model. In this analysis firstly the analysis has to properly
know about the association of dependent and independent variable. Moreover forecast a
linear trend. In this analysis shows the outliers or the extreme values of the variable and also
shows how much the predicted values are skewed by outliers. The third step is graphing the
variable which is relevant. In this process there are some factors which plays an important
role. These factors are R-square, adjusted R-square, values of coefficient and the critical
value. Moreover in this analysis try to show residuals plot, which shows the
heteroscadasticity of the model (Satterthwaite et al., 2013).
The other important way to improve a regression model is transformation. In this
process takes logarithm among all the variables which is positive and also takes standardized
scale on potential data range. Then transform the model in to multi-level model. In the
process of coefficients it is important that the estimated scale of coefficient has been taken in
smaller scale value. This can shows the smaller variation of the data (Fumo & Biswas, 2015).

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FINANCIAL AND COST ANALYSIS
Yes the model in the above question there is only a single independent variable.
Another variable is missing.
Answer to the question 3
Table 1 multiple linear Regression Output (model 2)
The linear regression model for multiple variables is as below
Y = β0+β 1X 1+β 2X 2+ β 3X 3+ β 4X 4+ β 5X 5+ β 6X 6+ β 7X 7+ β 8X 8+ β 9X 9
Where
Y= Sale price
X1= Lot area
X2= Land slope
X3= Year built
X4= Full bath

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FINANCIAL AND COST ANALYSIS
X5= Bedroom
X6= Garage cars
X7= Pool area
X8= Total Bsmt SF
X9= Half bath
Yes. This model helps to show and compare that the quality or relationship with
model 1. The multiple regression model is a better model as compared to model 1 linear
regression model, because in the multiple model there are more independent variables. No, all
the result of the model are properly and welly determined.
Answer to the question 4
It is to recommend that to increase the independent variable. Thus this means that
when the independent variables are increased then the model is good and shows a strong
relationship with the independent variable.
If the developer grading the land cost $10,000 per lot then the price of land increases.
At that situation land sale decreases. They should not grading the land.

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FINANCIAL AND COST ANALYSIS
References and bibliography
Cameron, A. C., & Trivedi, P. K. (2013). Regression analysis of count data (Vol. 53).
Cambridge university press.
Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. John Wiley & Sons.
Fumo, N., & Biswas, M. R. (2015). Regression analysis for prediction of residential energy
consumption. Renewable and sustainable energy reviews, 47, 332-343.
Satterthwaite, T. D., Elliott, M. A., Gerraty, R. T., Ruparel, K., Loughead, J., Calkins, M.
E., ... & Wolf, D. H. (2013). An improved framework for confound regression and
filtering for control of motion artifact in the preprocessing of resting-state functional
connectivity data. Neuroimage, 64, 240-256.