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MAE256 - Analytical Methods in Economics and Finance

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Added on  2020-02-24

MAE256 - Analytical Methods in Economics and Finance

   Added on 2020-02-24

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MAE256 T2 2017 –AssignmentSTUDENT ID[Pick the date]
MAE256 - Analytical Methods in Economics and Finance_1
Question 1 Descriptive statistics - House sale prices Interpretation Mean- The mean figure represents that the average price per house based on the given samplecomes out to be $ 804,880. Mean is typically the measure of central tendency and used as anaverage when there are not many outliers. In the given case, mean seems a reasonablerepresentation of the central value.Median- The median figure represents the price below which 50% of the houses have been soldin the given city of USA. This value is $798,960 which implies that half of the houses are soldbelow this price and half above this price. It is noticeable that the deviation between mean andmedian is minimal which augers well for the distribution which closely resembles a normaldistribution.Standard deviation – This represents the variation in the sale prices of the houses. It is apparentthat this value is $137,130 which implies that the variation of the data is low. This inference isalso supported through other measures of variation indicated in the summary statistics.1
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Skewness- Skew is a critical parameter which tends to be determine the shape of the distribution.A positive skew indicates a rightward shift while a negative skew indicates a leftward shift. Forthe given data, the skew is almost zero as it only 0.09 which represents a slight tail towards theright. Question 2 Mean = 804.88 Standard deviation = 137.13One-standard deviation from the mean house prices:Upper range ¿Mean+(1∗Standarddeviation)¿804.88+(1∗137.13)=942.007Lower range ¿Mean−(1∗Standarddeviation)¿804.88−(1∗137.13)=667.75Number of houses for which the house sale prices are fall within this range (667.75 942.007) =638 Total number of houses = 1000Proportion of houses with the sale price within one-standard deviation from the mean houseprices ¿6381000=0.638Question 3 Graphical representation Sale price of houses against size of house 2
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Independent variable: Size of house Dependent variable: Sale price of house 130.000140.000150.000160.000170.000180.000190.000200.000210.000220.0000.000200.000400.000600.000800.0001000.0001200.000Scatter plot : Size - Price Size (Square meters) Price(thousands$)Correlation coefficient = 0.59 It is apparent from the above scatter plot coupled with the correlation coefficient that there is apositive relationship of moderate strength between the size and price of the house sold. Hence, asa general rule if the house size increases, the price would increase not necessarily linearly andwould have some exceptions. Sale price of houses against proximity Independent variable: Proximity Dependent variable: Sale price of house 3
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