37 lines
1001 B
Python
37 lines
1001 B
Python
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#https://gist.github.com/cartr/6513044
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# Define the data
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# A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and a is the intercept (the value of y when x = 0).
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data = set()
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count = int(input("Enter the number of data points: "))
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for i in range(count):
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x=float(input("X"+str(i+1)+": "))
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y=float(input("Y"+str(i+1)+": "))
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data.add((x,y))
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# Find the average x and y
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avgx = 0.0
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avgy = 0.0
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for i in data:
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avgx += i[0]/len(data)
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avgy += i[1]/len(data)
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# Find the sums
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totalxx = 0
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totalxy = 0
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for i in data:
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totalxx += (i[0]-avgx)**2
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totalxy += (i[0]-avgx)*(i[1]-avgy)
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# Slope/intercept form
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m = totalxy/totalxx
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b = avgy-m*avgx
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print("Best fit line:")
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print("y = "+str(m)+"x + "+str(b))
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x = float(input("Enter a value to calculate: "))
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print("y = "+str(m*x+b))
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