Describe about the Business Statistics for The Present Project.
Introduction
The present project is the analysis of the data we collected. The data was collected from four locations – Inner city, Outskirts of city, Suburbs and remote regions. The data regarding the oil prices were collected from equal number of locations. The brands of oils were Shell and Caltex. Data was collected from 224 stations, equally divided amongst the two stations.
The response variable of the study is the price of the unipacket petrol.
The independent variables are the station from which the petrol is being purchased and the location of the petrol station.
Research Question
The research question for the project is: Does location of the station affect the price of petrol?
Research Hypothesis
To answer the above research question three hypothesis were developed.
The hypothesis for the tests
Null Hypothesis: The station brand has no effect on the price of petrol
Alternate hypothesis: The station brand has an effect on the price of petrol.
Null Hypothesis: The Location of the station has no effect on the price of petrol
Alternate Hypothesis: The Location of the station has an effect on the price of petrol
Null Hypothesis: There is no effect of the station brand and the location of the petrol station on the price of petrol
Alternate Hypothesis: The station brand and the location of the petrol station is linked by the price of petrol.
Data Analysis
To answer the above question we used the two factorial ANOVA.
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Between-Subjects Factors
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|
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Value Label
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N
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Brands
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1
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S
|
112
|
|
2
|
NS
|
112
|
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Locations
|
1
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Inner City
|
56
|
|
2
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Outskirts of City
|
56
|
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3
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Suburbs
|
56
|
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4
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Remote Region
|
56
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Table 1: Frequency of Station brand and Location of the petrol station
(source created by author)
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Descriptive Statistics
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Dependent Variable: UN
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Brands
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Locations
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Mean
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Std. Deviation
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N
|
|
S
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Inner City
|
114.9393
|
7.74570
|
28
|
|
Outskirts of City
|
107.9000
|
.00000
|
28
|
|
Suburbs
|
114.7714
|
2.87632
|
28
|
|
Remote Region
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116.7000
|
6.65488
|
28
|
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Total
|
113.5777
|
6.22869
|
112
|
|
NS
|
Inner City
|
108.3393
|
2.08581
|
28
|
|
Outskirts of City
|
121.1857
|
5.79180
|
28
|
|
Suburbs
|
115.7214
|
2.99448
|
28
|
|
Remote Region
|
115.6750
|
5.97406
|
28
|
|
Total
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115.2304
|
6.41218
|
112
|
|
Total
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Inner City
|
111.6393
|
6.53271
|
56
|
|
Outskirts of City
|
114.5429
|
7.83565
|
56
|
|
Suburbs
|
115.2464
|
2.94840
|
56
|
|
Remote Region
|
116.1875
|
6.28719
|
56
|
|
Total
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114.4040
|
6.36105
|
224
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Table 2: Descriptive statistics of the price of petrol based on the Station brand and Location of the station
(source created by author)
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Tests of Between-Subjects Effects
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Dependent Variable: UN
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|
Source
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Type III Sum of Squares
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df
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Mean Square
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F
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Sig.
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Partial Eta Squared
|
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Corrected Model
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3755.322a
|
7
|
536.475
|
21.997
|
.000
|
.416
|
|
Intercept
|
2931774.564
|
1
|
2931774.564
|
120211.155
|
.000
|
.998
|
|
Brands
|
152.955
|
1
|
152.955
|
6.272
|
.013
|
.028
|
|
Locations
|
646.995
|
3
|
215.665
|
8.843
|
.000
|
.109
|
|
Brands * Locations
|
2955.371
|
3
|
985.124
|
40.393
|
.000
|
.359
|
|
Error
|
5267.925
|
216
|
24.389
|
|
|
|
|
Total
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2940797.810
|
224
|
|
|
|
|
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Corrected Total
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9023.246
|
223
|
|
|
|
|
|
a. R Squared = .416 (Adjusted R Squared = .397)
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Table 3: Between subject effects of the price of petrol based on the Station brand and Location of the station
(source created by author)
From table 3 we find that there are statistically significant interaction between the station brand of petrol and the location of the petrol station, F(3,216)= 40.393, p = 0.000.
We also find that there are statistically significant differences between the station brand and the price of petrol F(1,216)=6.272, p = 0.013.
In addition, we also find that there are statistically significant differences between the location of the petrol station and the price of the petrol F(3,216) = 8.843, p = 0.000.
![The price of petrol based on station brand and location of the station]()
Figure 1: The price of petrol based on station brand and location of the station
(source created by author)
From figure 1 and table 2 we find that the price of station brand “S” petrol is the lowest at the outskirts of the city, and the highest at the remote region. The price of station brand “NS” is the highest at the outskirts of the city and the lowest at the inner city location.
Conclusion
From the above analysis we find that the price of unipacket petrol varies with the location and the brand of petrol station.
