Curve Fitting Metod || How to Fit a linear Curve

In this video, we will explore the method of curve fitting, specifically for linear curves. Curve fitting is a mathematical technique used to find the best fit of a function to a set of data points. Linear curve fitting is a common application of curve fitting where we try to find the best linear relationship between two variables.
We will discuss the method of least squares, which is widely used for linear curve fitting. This involves finding the line that minimizes the sum of the squared distances between the predicted values of the line and the actual data points. We will walk you through the steps of using this method, including plotting the data points, choosing a linear model, calculating the sum of squared errors, and adjusting the values of the slope and y-intercept to minimize the sum of squared errors.
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regression equation:
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Simpson 1/3 rule Trigonometric equation:
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Curve fitting method (exponential equation):
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Curve fitting
Linear curve fitting
Least squares method
Regression analysis
Statistics
Mathematics
Modeling techniques
Fitting curves to data
Trend analysis
Graphing data
Statistical analysis
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0:00 intro
1:00 Solution begins
2:35 Unknowns Calculation
5:15 Calculate A and B
8:09 required Equation
8:23 How to solve Liner Equation Manually
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