What you’ll learn
Fit linear models to data.
Key idea
Slope is output change per input unit; vertical residual is observed minus predicted output.
Fit uses all observations; better of two candidates is not a claim of global least-squares optimality.
Worked example
Enter the exact value or ordered values in the format requested below.
Exact linear table [(0, 6), (1, 10), (2, 14)]. Write the fitted equation y=mx+b.
- Exact table [(0, 6), (1, 10), (2, 14)] has value 6 at input zero and output change 4 per unit input.
- Equation y=4x+6 matches all three points; interchanging slope and intercept gives y=6x+4, which fails the zero-input point.
Answer: y=4x+6
Quick Check
Choose which candidate representation satisfies the requirements of 'Fit linear models to data' and justify the choice.
For measured data [(0, 7), (1, 10), (2, 14)], compare candidates A: y=3x+7; B: y=4x+7 by total squared vertical residuals. Choose with BOTH totals.