Gross Fixed Capital Formation per Capita in 2007 (Yuan)
(X-MeanX)2
(Y- MeanY2)
(x-MEANX)
(Y-MeanY)
(x-MEANX)(y-MEANY)
Y
X
Beijing
58204
25000.37
200145595
1312654974
14147.2823
36230.5806
512564250.8
Tianjin
46122
24047.98
174105182
583153947.2
13194.8923
24148.5806
318637919.8
Hebie
19877
8947.05
3632979.87
4394974.111
-1906.0377
-2096.4194
3995854.413
Shanxi
16945
8575.33
5188180.33
25285001.21
-2277.7577
-5028.4194
11453521.12
Inner Mongolia
25393
18113.89
52719249.4
11693531.79
7260.80226
3419.58065
24828898.87
Liaoning
25729
14032.81
10110633.6
14104385.98
3179.72226
3755.58065
11941703.37
Jilan
19383
14663.66
14520460.9
6710272.434
3810.57226
-2590.4194
-9870980.13
Heilongjiang
18478
7525.73
11071309.5
12217956.47
-3327.3577
-3495.4194
11630510.65
Shanghai
66367
27133.48
265051172
1970790002
16280.3923
44393.5806
722744906.6
Jiangsu
33928
15206.06
18948367.5
142911998.4
4352.97226
11954.5806
52037957.91
Zhejiang
37411
16208.06
28675727.9
238318896.2
5354.97226
15437.5806
82667816.09
Anhui
12045
5469.53
28982694
98573510.89
-5383.5577
-9928.4194
53450218.88
Fujian
25908
12133.15
1638559.38
15480924.85
1280.06226
3934.58065
5036508.185
Jiangxi
12633
6154.6
22075787.1
87243433.72
-4698.4877
-9340.4194
43885845.84
Shangdong
27807
12580.94
2985473.43
34030663.14
1727.85226
5833.58065
10079565.49
Henan
16012
8593.32
5106550.25
35538520.72
-2259.7677
-5961.4194
13471423.15
Hubei
16206
7670.01
10131983.9
33263126.01
-3183.0777
-5767.4194
18358144.18
Hunan
14492
6208.42
21572938.4
55971635.56
-4644.6677
-7481.4194
34748707.14
Guangdong
33151
10499.51
125017.22
124938309.1
-353.57774
11177.5806
-3952143.72
Guangxi
12555
5938.8
24150224
88706623.14
-4914.2877
-9418.4194
46284822.78
Hainan
14555
5863.91
24891894.5
55032945.72
-4989.1777
-7418.4194
37011812.73
Chongqing
14660
9189.84
2766393.05
53486102.66
-1663.2477
-7313.4194
12164028.23
Sichuan
12893
6159.04
22034084.2
82454015.66
-4694.0477
-9080.4194
42623921.97
Guizhou
6915
3619.86
52319583.6
226755993.5
-7233.2277
-15058.419
108920976.6
Yunnan
10540
5797.01
25563922.1
130723078.1
-5056.0777
-11433.419
57808257.11
Tibet
12109
9565.85
1656981
97306769.21
-1287.2377
-9864.4194
12697852.9
Shaanxi
14607
8410.57
5965892.92
54264134.11
-2442.5177
-7366.4194
17992609.97
Gansu
10346
4669.32
38238983.5
135196880.9
-6183.7677
-11627.419
71901260.73
Qinghai
14257
8703.44
4620985.41
59543127.66
-2149.6477
-7716.4194
16587583.44
Ningxia
14649
10193.77
434699.885
53647118.89
-659.31774
-7324.4194
4829119.63
Xinjiang
16999
9570.41
1645262.19
24744847.92
-1282.6777
-4974.4194
6380576.986
Total
1081076768
5869137702
2352913452
Section 1.1
From the above calculation, it can be said that;
Y
X
Mean
21973.4194
10853.0877
Median
16206
8947.05
Range
59452
23513.62
From the calculation of the Mean value of X, it can be observed that which provinces lie in the upper quartile which is Mongolia, Zhejiang, Beijing, Tianjin, Liaoning, Jilan, Shanghai, Jiangsu, Fujian and Shangdong. Moreover, from the abobe table, it can be observed that the dispersion in the two variables across regions is higha as the range of the both the variables that are Gross Regional Product per Capita 2007 and Gross Fixed Capital Formation per Capita in 2007 varies a lot.
For Gross Regional Product per Capita 2007, the regions that lie in the lower quartile are Mongolia, Zhejiang, Beijing, Tianjin and Liaoning; however, for Gross Fixed Capital Formation per Capita in 2007 the regions that lie in the lower quartile are Jilan, Shanghai, Jiangsu, Fujian and Shangdong.
Variance of X
=
1081076768/31
=
34873444.14
Variance of Y
=
5869137702/31
=
189327022.6
Standard Deviation of X =
Square root of variance of X =
5905.374174
Standard Deviation of Y =
Square root of variance of Y =
13759.61564
The values of the standard deviations and the mean of X and Y reflects that how further away is the data set from the mean and with the calculated result, it can be observed that the data set is very close to the Mean value.
Section 1.2
Covariance of XY
(X-MEAN OF X)(Y-MEAN OF Y)/N-1
Cov (x,y)
=
2352913452
31
Cov (x,y)
=
75900433.9
Correlation
75892804
=
0.934
5905.37417
x
13759.61564
75892804
=
0.934
81255678.8
From the calculation of the correlation, it is observed that there is a strong positive relationship between X and Y, reflecting as increase in the value of Y will increase the value of X which shows positive relationship between the variables.
Correlations
VAR00001
VAR00002
Gross Regional Product per Capita 2007 (Yuan)
Pearson Correlation
1
.934 **
Sig. (2-tailed)
.000
N
31
31
Gross Fixed Capital Formation per Capita in 2007 (Yuan)
Pearson Correlation
.934 **
1
Sig. (2-tailed)
.000
N
31
31
**. Correlation is significant at the 0.01 level (2-tailed).
The above result for the data shows that there is correlation between Gross Regional Product per Capita 2007 (Yuan) and Gross Fixed Capital Formation per Capita in 2007 (Yuan). In addition to this, the value of the Pearson correlation coefficient shows that the value is in positive that is 0.934 as the value of Pearson correlation coefficient is significant that is it is are less than 0.05 which shows that the value is significant. Therefore, it can be said that there is a relationship between the two variables. In addition to this, the correlation between the variables is high as the value of Pearson Correlation is above 0.5 which reflecst that that more the value of the Pearson Correlation is graeter the more correlation exist between the variables.
Section 1.3
(a)
A common statistical way of standardizing data on one scale so a comparison can take place is using a z-score. The z-score is like a common yard stick for all ...