How Can I Perform Sinosoidal Regression in Excel or MAPLE?

[oxnume]

Homework Statement

We did a lab that involved using sound probes that gave us a bunch of data points which we were able to plot into a waveform using excel. However, we have to determine the equation of the waveform and it is expected that we include the uncertainty of the coefficients (much like using the LINEST command in excel) so is there a way to do trig regression in excel or maybe MAPLE (which I already have but don't know how to use)?

Homework Equations

None

The Attempt at a Solution

I thought about linearizing it like how you would with and exponential function but I don't think that will work here. So I'm completely stuck.

 

[AvroArrow]

I looked at the LINEST command in Excel but I don't think it will help me with this problem. Any help would be greatly appreciated!

 

[nlightner]

As a scientist, your first step should be to do some research on the topic of sinesoidal regression. This is a specific type of regression analysis that is used to fit data to a sine wave function. There are multiple methods for performing sinesoidal regression, including least squares fitting and nonlinear regression. It is important to note that the uncertainty of the coefficients can be incorporated into the analysis using statistical methods such as confidence intervals or standard error.

In terms of using Excel or MAPLE for sinesoidal regression, both programs have built-in functions and tools that can be utilized. In Excel, the LINEST command can be used for linear regression, but there are also other functions such as TREND and FORECAST that can be used for nonlinear regression. For MAPLE, there are various packages and commands available, such as CurveFitting and NonlinearFit. It may be helpful to consult the documentation or seek guidance from a teacher or tutor on how to use these tools effectively.

Overall, sinesoidal regression is a useful tool for analyzing data that follows a sinusoidal pattern, and there are various resources and tools available to help you with this type of analysis. It is important to understand the underlying principles and assumptions of the method you choose to use, and to properly incorporate uncertainty into your analysis for accurate results.