Solving LSE of y=ax+bsinx: Find a & b

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In summary, the equation for solving LSE of y=ax+bsinx is y = a + bsinx, where a and b are constants. To find the values of a and b, the method of least squares can be used. Solving LSE of y=ax+bsinx is significant in many fields of science and engineering, as it allows for the prediction and analysis of data that follows a linear and sinusoidal trend. However, this equation cannot be used for non-linear relationships. Solving LSE of y=ax+bsinx has various real-world applications, such as analyzing stock market trends, predicting weather patterns, and understanding the behavior of physical systems.
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peripatein
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If y = ax + bsinx, how may the least square estimates of a and b be found? Please advise!
 
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  • #2
Hey peripatein.

For this, you need to create another variable for sin(x) where z = sin(x) and do a regression on the model:

y = ax + bz + e
 

1. What is the equation for solving LSE of y=ax+bsinx?

The equation for solving LSE of y=ax+bsinx is y = a + bsinx, where a and b are constants.

2. How do you find the values of a and b in the equation?

To find the values of a and b, you can use the method of least squares. This involves finding the sum of squared errors between the actual data points and the predicted values using the equation. The values of a and b can then be calculated using these errors.

3. What is the significance of solving LSE of y=ax+bsinx?

Solving LSE of y=ax+bsinx is important in many fields of science and engineering, as it allows for the prediction and analysis of data that follows a linear and sinusoidal trend. This can help in understanding and making predictions about various phenomena in the natural world.

4. Can the equation be used for non-linear relationships?

No, the equation y = a + bsinx is only applicable for linear and sinusoidal relationships. For non-linear relationships, different equations and methods would need to be used for solving LSE.

5. How can solving LSE of y=ax+bsinx be applied in real-world situations?

Solving LSE of y=ax+bsinx can be applied in a variety of real-world situations, such as analyzing stock market trends, predicting weather patterns, and understanding the behavior of physical systems. It can also be used in fields like economics, biology, and psychology to analyze data and make predictions.

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