Instructions for essay preparation and submission Instructions for preparation 1. Access theclient profile and Excel data file for the case study provided. 2. Carefully read all materials provided...

Introduction
    Introduction
    This is the Excel file prepared by AveNew Real Estate for your data analysis. You'll notice that there are four tabs (not including this one) of data analysis required.
    The tabs are:
    Property type distribution (contains content from week 2; 15 marks available)
    Sale price influences (contains content from weeks 2, 3 and 5; 45 marks available)
    Probability of sale locations (contains content from week 3; 15 marks available)
    Average sale price analysis (contains content from weeks 4 and 5; 25 marks available)
    As well as providing an essay reporting AveNew Real Esate on your findings and interpretations, you should also provide your Excel data analysis.
    You can provide your data analysis in this file.
    There will be 15 extra marks available for essay quality (10 marks) and presentation of the Excel file (5 marks).
Property type distribution
    Property types in Melbourne's North                                                                    Property type    Price            Bin range    Bin range    Frequency    relative frequency    Cumulative %
                                                                        Apartment    $ 750,000.00            $ 500,000.00    0-500000    1    0.11    11.11%
    As AveNew Real Estate predominantly work within the northern suburbs of Melbourne, they are interested to know the current property types available for sale.                                                                    House     $ 1,050,000.00            $ 1,000,000.00    500000-1000000    2    0.22    33.33%
    You are asked to research the various property types in Melbourne's north, and then present your findings by generating:                                                                    House     $ 2,200,000.00            $ 1,500,000.00    1000000-1500000    3    0.33    66.67%
    a) a frequency distribution                                                                    Apartment    $ 499,000.00            $ 2,000,000.00    1500000-2000000    2    0.22    88.89%
    b) a relative frequency distribution                                                                    House     $ 975,000.00            $ 2,500,000.00    2000000-2500000    1    0.11    100.00%
    c) illustrate both distributions above using appropriate graph types. Why have you chosen these graph types?                                                                    TownHouse    $ 1,769,000.00                More    0        100.00%
                                                                        TownHouse    $ 1,959,000.00
    AveNew ask that the property types presented in the distributions are as follows:                                                                    House     $ 1,200,000.00
    House                Property Type    Count of Property type                                                TownHouse    $ 1,495,000.00
    Apartment/Unit                Apartment    2
    Townhouse                House     4
    Land                TownHouse    3
    Other                Grand Total    9
    Interpret your results. What do these results implicate for AveNew Real Estate in terms of which properties they should primarily focus on selling?
    AveNew are happy for you to conduct your research anywhere you like, but if you are stuck, they suggest looking at popular Australian property websites, such as RealEstate.com.au or Domain.com.au.
    Remember to source where you have found your information!
relative frequency    
0-500000    500000-1000000    1000000-1500000    1500000-2000000    2000000-2500000    0.1111111111111111    0.22222222222222221    0.33333333333333331    0.22222222222222221    0.1111111111111111    
Frequency distribution
Frequency    
0-500000    500000-1000000    1000000-1500000    1500000-2000000    2000000-2500000    1    2    3    2    1    
We have fetched price and type of property data from domain.com.au. the frequency distribution of price has shown that most frequent type of property to be sold is house. Second most frequent property to be sold is townhouse. Apartments units are least frequent property to be sold in Melbourne northern.
We have also drawn frequency of properties by their selling price. Price range of 1000000 to 1500000 has 33.34 percent of total property listed to be sold. Price range 0-500000 and 2000000-2500000 has 11 percent each of total property listed on portal to be sold.
Sale price influences
    Which factors most influence house sale price?                                        Summary Statistics    Sale price ($'000)    Land size (m2)    Distance from CBD (km)    Age of home (years)    Number of bedrooms    Money spent on styling ($'000)
    Listed below are the details of eight various properties that have recently been sold by AveNew Real Estate.                                        Mean    837.00    651.00    14.20    7.70    3.60    10.90
                                            Standard Error    89.52    47.85    1.87    1.12    0.16    1.53
    Property    Sale price ($'000)    Land size (m2)    Distance from CBD (km)    Age of home (years)    Number of bedrooms    Money spent on styling ($'000)                Median    730.00    625.00    13.50    6.50    4.00    10.00
    1    670    580    10    8    3    4                Mode    ERROR:#N/A    620.00    10.00    5.00    4.00    10.00
    2    780    760    12    5    4    15                Standard Deviation    283.08    151.32    5.92    3.53    0.52    4.84
    3    660    620    20    10    4    10                Sample Variance    80134.44    22898.89    35.07    12.46    0.27    23.43
    4    650    340    25    4    3    15                Kurtosis    0.50    1.92    -0.67    0.34    -2.28    0.02
    5    530    620    15    15    4    10                Skewness    1.23    -0.31    0.59    0.94    -0.48    0.41
    6    790    640    20    10    3    5                Range    870.00    580.00    18.00    11.00    1.00    16.00
    7    680    620    15    10    3    12                Minimum    530.00    340.00    7.00    4.00    3.00    4.00
    8    1,250    780    7    5    4    10                Maximum    1400.00    920.00    25.00    15.00    4.00    20.00
    9    960    630    10    5    4    8                Sum    8370.00    6510.00    142.00    77.00    36.00    109.00
    10    1,400    920    8    5    4    20                Count    10.00    10.00    10.00    10.00    10.00    10.00
                                            Quartile 1    657.50    610.00    9.50    5.00    3.00    7.25
                                            Quartile 3    1032.50    765.00    20.00    10.00    4.00    15.00
                                            IQR    375.00    155.00    10.50    5.00    1.00    7.75
                                            Coeffcient of variation    0.34    0.23    0.42    0.46    0.14    0.44
                                            Confidence Level(95.0%)    202.50    108.25    4.24    2.52    0.37    3.46
    For each variable, find the following:                            375
    (NOTE: You may use Excel to find the following, but you must demonstrate that you know how to work these out manually using the sale price data in your report)                                                        Correletion Matrix    Sale price ($'000)    Land size (m2)    Distance from CBD (km)    Age of home (years)    Number of bedrooms    Money spent on styling ($'000)
    1. The mean, median and mode - interpret what these values tell you about the data. Is there any skew in these data?                                                        Sale price ($'000)    1.00
    2. The lower and upper quartile, and the interquartile range - interpret what these values tell you about the data.                                                        Land size (m2)    0.74    1.00
    3. Provide a box and whisker plot for sale price - interpret what this graph tells you about the data, i.e. are...