Statistic: Statistical Hypothesis Testing and Real Estate Data

1. First enter the Real estate data (text book data set 1) into SPSS and then select a sample of size, n = last two digits of your ID and answer the exercises.

I. Select an appropriate class interval and organize the “Selling price” into a frequency distribution.
II. Compute the Mean, Median, Mode, Standard Deviation, Variance, Quartiles, 9th Decile, 10th Percentile and Range of “Selling price” from the raw data of your sample and interpret.
III. Develop a histogram (Using question “1”) for the variable “selling cost”.
IV. Develop a Pie chart and a Bar diagram for the variable “Township”.
V. Develop a Box plot for the variable “Distance”. What information can you give from these plots?

Note: Comment on all your findings, charts and diagrams.

Answer to the question No.1

I. Selection of an appropriate Class interval

We select a sample size of n = 39 (last two digits of ID: 39)
To determine the number of Classes (k)
2 ≥ n
2≥ 64
So the recommended number of classes is 7.
Selling Price in TK. 000 (Thousand)
N
Valid
39

Missing
0
Minimum
1390.9
Maximum
3450.3

Class interval
So 343.233300
So the class intervals are,
1→1300 ─ 1600
2→1600─1900
3→1900─2200
4→2200─2500
5→2500─2800
6→2800─3100
7→3100─3400
8→3400-3700

From SPSS output, we get the following frequency distribution of selling price of homes sold in Denver, Colorado: Frequency Distribution of Selling Price of the homes sold in Denver
Class interval of the selling price
Frequency
Percent
Valid Percent
Cumulative Percent
Valid

1300-1600
2
5.1
5.1
5.1

1600-1900
8
20.5
20.5
25.6

1900-2200
13
33.3
33.3
59.0

2200-2500
9
23.1
23.1
82.1

2500-2800
3
7.7
7.7
89.7

2800-3100
2
5.1
5.1
94.9

3100-3400
1
2.6
2.6
97.4

3400-3700
1
2.6
2.6
100.0

Total
39
100.0
100.0

Comment: The selling price of maximum homes (13) or 33.3% homes falls in the 1900-2200 range. The selling