DATA:

date	house	gdp	interest
5/15/2002	6.87309	3.567727	5.515236
8/15/2002	4.109163	0.978795	4.995225
11/15/2002	2.961117	5.423882	4.869358
2/15/2003	0.001663	-8.33886	3.949507
5/15/2003	4.458599	3.519417	5.059033
8/15/2003	4.363868	1.757381	4.787134
11/15/2003	3.559352	7.508813	5.241011
2/15/2004	-1.77336	-7.64669	4.698297
5/15/2004	-4.21497	3.802526	5.370114
8/15/2004	-0.957	1.335485	5.198758
11/15/2004	-0.27107	5.777947	4.602777
2/15/2005	-2.84392	-7.55266	4.731204
5/15/2005	-1.9248	4.582637	4.691053
8/15/2005	-2.66549	1.452142	4.22991
11/15/2005	0.383516	6.3435	4.91435
2/15/2006	-1.81332	-8.43442	4.436944
5/15/2006	0.195047	3.106712	4.032395
8/15/2006	-0.8101	2.291104	4.805018
11/15/2006	0.599602	6.679772	5.76904
2/15/2007	-0.24096	-6.4464	5.8079
5/15/2007	2.594526	3.831032	4.741592
8/15/2007	1.75771	0.734607	5.338449
11/15/2007	1.477653	5.654151	5.229798
2/15/2008	-1.90113	-8.40132	4.805332
5/15/2008	-2.77744	5.124434	4.931121
8/15/2008	-3.46076	1.81273	4.757427
11/15/2008	-1.29487	4.589894	5.114191
2/15/2009	-1.75335	-9.12946	4.113942
5/15/2009	4.466014	2.094695	4.591901
8/15/2009	3.47313	-0.78079	4.47945
11/15/2009	5.028565	5.666131	4.930284
2/15/2010	2.351384	-7.38068	4.597266
5/15/2010	2.069748	7.19547	4.903915
8/15/2010	-1.0228	0.404348	4.308478
11/15/2010	-0.60982	5.12644	4.924659
2/15/2011	-1.73833	-8.40839	4.076878
5/15/2011	-0.71929	6.170844	4.416935
8/15/2011	-2.5637	0.669862	3.966828
11/15/2011	-1.1988	3.757904	4.0925
2/15/2012	0.708697	-8.26666	3.871466
5/15/2012	1.004013	5.402672	2.876166
8/15/2012	-1.69086	-2.12252	1.661411
11/15/2012	2.281237	3.75929	2.916036
2/15/2013	0.768385	-7.6672	3.07701
5/15/2013	3.337864	4.972977	2.946042
8/15/2013	2.98015	-1.1022	2.701018
11/15/2013	5.336964	4.785339	3.343269
2/15/2014	1.17894	-7.95315	3.562481
5/15/2014	3.460043	3.561437	3.36145
8/15/2014	2.445838	-1.22822	3.002023
11/15/2014	3.413563	4.324454	2.988697
2/15/2015	3.584572	-7.54435	2.353216
5/15/2015	9.109359	3.23635	2.099569
8/15/2015	2.846572	-0.20878	2.305717
11/15/2015	-2.50739	3.377668	2.402963
2/15/2016	-0.39353	-7.16959	2.773669
5/15/2016	2.795689	5.264798	1.947814
8/15/2016	2.20637	-0.74237	1.192518
11/15/2016	5.534279	6.743221	1.950721
2/15/2017	2.469766	-6.73855	2.307955
5/15/2017	1.935996	3.979979	2.322338
8/15/2017	-1.94167	-0.49026	2.014327
11/15/2017	-0.84948	3.682684	2.014967
2/15/2018	-1.83107	-6.28961	2.330636
5/15/2018	-1.59119	5.189821	2.388094
8/15/2018	-2.54714	-0.36878	2.177522
11/15/2018	-4.42172	4.347746	2.068032
2/15/2019	-4.23216	-6.22962	2.12
5/15/2019	-0.80289	5.109959	1.016503
8/15/2019	3.462172	-0.40122	0.574019
11/15/2019	4.477075	2.737958	0.433426
2/15/2020	2.258426	-7.44312	0.662433
5/15/2020	-0.76259	-1.76822	2.783459
8/15/2020	-0.12583	1.587054	-0.68343
11/15/2020	3.077771	7.743045	0.029415
2/15/2021	7.365388	-4.75805	0.756064

The 'house price' data set has three variables:

'house': the growth rate in percentage of real price of houses in Sydney. For example, an observation of 2 would mean that house price has increased by 2% over the time period.

'gdp': the growth rate in percentage of Australian real gdp per capita

'interest': the growth rate in percentage of the real interest rate that is represented by the yield of 10-year Australian government bonds.

REQUIREMENT: Deliver a REPORT answering below questions (analyze and make comment)

IMPORTANT: **PLEASE, INCLUDE EXCEL FULL CALCULATION**

This question investigates the statistical properties of the house price growth rate represented

by variable 'house' in data set 'house price'.

a) Make a histogram of house price growth rate and comment on the shape of the

distribution

Please use 'bins' (categories) of length 0.5 when create the histogram. That is, the bins

should have categories of -4.50 - -4.00, -4.00- -3.50, etc up to 9.00-9.50.

Your chart should include a chart heading and axis titles.

b) Compute the following statistics for house price growth:

mean,

median,

standard deviation,

maximum, minimum, range,

upper quartile, lower quartile and inter quartile range

mean absolute deviation

c) Construct a 95% confidence interval for house price growth

d) Estimate the probability of having a house price growth rate lower than -1% (i.e. values

in the provided spreadsheet lower than -1). Compute this by estimating the proportion

of the observations where house price growth was less than -1%.

e) Using the method covered in the textbook for detecting outliers, compute the cutoff

value of the house price growth rate below which an observation would be deemed an

outlier.

f) What proportion of the observations in the data set would be considered outliers based

on the cutoff value for outlier detection