Statistics for Financial Decisions | Assignment

Running head: STATISTICS FOR FINANCIAL DECISIONS
Statistics for Financial Decisions
Name of the University:
Name of the student:
Authors Note:

STATISTICS FOR FINANCIAL DECISIONS1
Table of Contents
a) Introduction:...........................................................................................................................2
b) Relationship between dependent and independent variables using scatterplots....................2
Fig 1. Scatter Plot between age of house and market price...................................................2
Fig 2. Scatter plot between price index and the market price................................................3
Fig 3. Scatter plot between Area and Market Price...............................................................3
c) Multiple Regression Summary Statistics:..............................................................................4
e) Slope of simple linear regression:..........................................................................................5
f) Co-efficient of determination for simple linear regression:...................................................6
g) 95% confidence interval for the slope coefficient................................................................6
h) Goodness of fit.......................................................................................................................6
i) Predicting Market Price..........................................................................................................6
j) Hypothesis Test......................................................................................................................7
References:.................................................................................................................................9

STATISTICS FOR FINANCIAL DECISIONS2
a) Introduction:
The data of 400 variables all related to the real estate sector is given. The variables are
Property Id, Market Price of house in dollars, Property Index, Size of house in square metres
and Age of the house in years. Generally, in the real estate industry, the price of a house of
increases with increase in size of the house. And the more the age of the house the lesser its
price due to depreciation. The price of a house is dependent on many other factors such as the
neighbourhood, the number of bedrooms, the price index, local taxes etc(Ihlanfeldt, 2007). In
this report, the data is calculated for four parameters. Out of the 400 data entries, 50 random
samples are selected with the aid of a random number table.
The OLS regression is used for estimating if there is any relationship between, the market
price of a house and the other variables. The market price is taken as the response variable
and the price index, size of the house and age of the house are taken as the explanatory
variables (Chatterjee and Hadi,2015).
b) Relationship between dependent and independent variables using scatterplots.
-5 0 5 10 15 20 25 30 35 40 45
0
100
200
300
400
500
600
700
800
900
1000
f(x) = 0.17 x + 758.05
R² = 0
Scatter Plot
Age
Market Price.
Fig 1. Scatter Plot between age of house and market price.
As R2 = 0.0009, therefore, it can be seen that there is a weak positive relationship
between the two variables and the change in one does not impact the other.

STATISTICS FOR FINANCIAL DECISIONS3
20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0
0
100
200
300
400
500
600
700
800
900
1000
f(x) = 0.16 x + 743.74R² = 0
Scatter Plot
Price Index
Market Price
Fig 2. Scatter plot between price index and the market price.
As R2 = 0.0009, therefore, it can be seen that there is a weak positive relationship
between the variable. Market price is affected very weakly by change in the price index.
50.0 100.0 150.0 200.0 250.0 300.0
0
100
200
300
400
500
600
700
800
900
1000
f(x) = 1.79 x + 402.2
R² = 1
Scatter Plot
Area
Market Price
Fig 3. Scatter plot between Area and Market Price
As R2= 0.9954, it can be seen that, there is a strong positive relationship between the
market price of a house and the size of the house.