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Implementation of Univariate Linear Regression

Aim:

To implement univariate Linear Regression to fit a straight line using least squares.

Equipment’s required:

  1. Hardware – PCs
  2. Anaconda – Python 3.7 Installation / Moodle-Code Runner

Algorithm:

  1. Get the independent variable X and dependent variable Y.
  2. Calculate the mean of the X -values and the mean of the Y -values.
  3. Find the slope m of the line of best fit using the formula. eqn1
  4. Compute the y -intercept of the line by using the formula: eqn2
  5. Use the slope m and the y -intercept to form the equation of the line.
  6. Obtain the straight line equation Y=mX+b and plot the scatterplot.

Program







Output





Result

Thus the univariate Linear Regression was implemented to fit a straight line using least squares.

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