Graph using the scatter plot diagram and interpret the following data.
71-80. The owner of a chain of fruit shake stores would like to study the correlation between atmospheric temperature and sales during the summer season. Suppose a random sample of 12 days is selected with the results given as follows:
Day
Temperature(F0)
(x)
Total Sales (Units)
(y)
1
79
147
2
76
143
3
78
147
4
84
168
5
90
206
6
83
155
7
93
192
8
94
211
9
97
209
10
85
187
11
88
200
12
82
150
A scatter diagram for the data given is obtained from entering the following commands in "R"
> x=c(79,76,78,84,90,83,93,94,97,85,88,82)
> y=c(147,143,147,168,206,155,192,211,209,187,200,150)
> plot(x,y,main="Scatter plot of sales against temperature")
These commands produces the scatter diagram below.
Clearly, the values of sales increases with increase in temperature. We can therefore predict that there is a strong positive correlation between sales and temperature. To verify this, we need to determine the correlation coefficient "r".
To obtain the value of the correlation coefficient, we enter the following commands in "R"
> x=c(79,76,78,84,90,83,93,94,97,85,88,82)
> y=c(147,143,147,168,206,155,192,211,209,187,200,150)
> cor(x,y)
[1] 0.9270573
The value of "r=0.9270573" shows that there is a strong positive correlation between sales and temperature.
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