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Substitute x value in a linear regression equation instead of writing it out?

Thanks to this handy post, I was able to generate a linear regression graph: http://stackoverflow.com/questions/454606/how-can-i-do-regression-analysis-in-sage

My input thus far in sage 5.9:

r = [[0,76.4], [1,78.5], [2,81.5], [3,87.8], [4,88.4], [5,92.4], [6,94.0], [7,95.0]] var('a,b') (a, b) //It seems this statement is extraneous model(x) = a*x+b find_fit(r, model) plot(model(a = find_fit(r, model)[0].rhs(), b = find_fit(r,model)[1].rhs()), 0,15, ymin = 0, ymax = 150)

What would be the most practical way of substituting the x value to generate an answer instead of:

Executing: find_fit(r, model) Then copying and pasting the answer: [a == 2.8690476152412128, b == 76.70833334665576]

And then having to manually write out, where number 15 represents what I wanted to put substitute for x: 2.8690476152412128 * (15) + 76.70833334665576

Substitute x value in a linear regression equation instead of writing it out?

Thanks to this handy post, I was able to generate a linear regression graph: http://stackoverflow.com/questions/454606/how-can-i-do-regression-analysis-in-sage

My input thus far in sage 5.9:

r = [[0,76.4], [1,78.5], [2,81.5], [3,87.8], [4,88.4], [5,92.4], [6,94.0], [7,95.0]] var('a,b') (a, b) //It seems this statement is extraneous model(x) = a*x+b find_fit(r, model) plot(model(a = find_fit(r, model)[0].rhs(), b = find_fit(r,model)[1].rhs()), 0,15, ymin = 0, ymax = 150)

What would be the most practical way of substituting the x value to generate an answer instead of:

Executing: find_fit(r, model) Then copying and pasting the answer: [a == 2.8690476152412128, b == 76.70833334665576]

And then having to manually write out, where number 15 represents what I wanted to put substitute for x: 2.8690476152412128 * (15) + 76.70833334665576

Also 1 of my other threads has an unsolved question, incase anyone's interested: http://ask.sagemath.org/question/2732/display-y-intercept

Substitute x value in a linear regression equation instead of writing it out?

Thanks to this handy post, I was able to generate a linear regression graph: http://stackoverflow.com/questions/454606/how-can-i-do-regression-analysis-in-sage

My input thus far in sage 5.9:

r = [[0,76.4], [1,78.5], [2,81.5], [3,87.8], [4,88.4], [5,92.4], [6,94.0], [7,95.0]]
var('a,b')
(a, b)     //It seems this statement is extraneous
model(x) = a*x+b
find_fit(r, model)
plot(model(a = find_fit(r, model)[0].rhs(), b = find_fit(r,model)[1].rhs()), 0,15, ymin = 0, ymax = 150)

150)

What would be the most practical way of substituting the x value to generate an answer instead of:

Executing: find_fit(r, model) Then copying and pasting the answer: [a == 2.8690476152412128, b == 76.70833334665576]

And then having to manually write out, where number 15 represents what I wanted to put substitute for x: 2.8690476152412128 * (15) + 76.70833334665576

Also 1 of my other threads has an unsolved question, incase anyone's interested: http://ask.sagemath.org/question/2732/display-y-intercept

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fixed preformatted text

Substitute x value in a linear regression equation instead of writing it out?

Thanks to this handy post, I was able to generate a linear regression graph: http://stackoverflow.com/questions/454606/how-can-i-do-regression-analysis-in-sage

My input thus far in sage 5.9:

r = [[0,76.4], [1,78.5], [2,81.5], [3,87.8],  [4,88.4], [5,92.4], [6,94.0], [7,95.0]]
var('a,b')
(a, b)     //It #It seems this statement is extraneous
model(x) = a*x+b
find_fit(r, model)
plot(model(a = find_fit(r, model)[0].rhs(),  b = find_fit(r,model)[1].rhs()),  0,15, ymin = 0, ymax = 150)

What would be the most practical way of substituting the x value to generate an answer instead of:

Executing: find_fit(r, model) Then copying and pasting the answer: [a == 2.8690476152412128, b == 76.70833334665576]

And then having to manually write out, where number 15 represents what I wanted to put substitute for x: 2.8690476152412128 * (15) + 76.70833334665576

Also 1 of my other threads has an unsolved question, incase anyone's interested: http://ask.sagemath.org/question/2732/display-y-intercept

Substitute x value in a linear regression equation instead of writing it out?

Thanks to this handy post, I was able to generate a linear regression graph: http://stackoverflow.com/questions/454606/how-can-i-do-regression-analysis-in-sage

My input thus far in sage 5.9:

r = [[0,76.4], [1,78.5], [2,81.5], [3,87.8], 
     [4,88.4], [5,92.4], [6,94.0], [7,95.0]]
var('a,b')
(a, b)    #It seems this statement is extraneous
model(x) = a*x+b
find_fit(r, model)
plot(model(a = find_fit(r, model)[0].rhs(), 
           b = find_fit(r,model)[1].rhs()), 
           0,15, ymin = 0, ymax = 150)

What would be the most practical way of substituting the x value to generate an answer instead of:

Executing: find_fit(r, model) Then copying and pasting the answer: [a == 2.8690476152412128, b == 76.70833334665576]

And then having to manually write out, where number 15 represents what I wanted to put substitute for x: 2.8690476152412128 * (15) + 76.70833334665576

Also 1 of my other threads has an unsolved question, incase anyone's interested: http://ask.sagemath.org/question/2732/display-y-intercept