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engineer23
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I have two data sets and want to do a regression so that the equation that relates them is of the form y = C(x^n), where C and n are constants.
How do I do this in Excel?
How do I do this in Excel?
engineer23 said:I have two data sets and want to do a regression so that the equation that relates them is of the form y = C(x^n), where C and n are constants.
How do I do this in Excel?
statdad said:Of course, there is the question of why Excel would be used for regression in the first place.
statdad said:No, it does not.
ssd said:?? Whatever the model (of the two you considered) may be, after taking log on both sides, what remains to convert the the model to the common one is to suitably rename the variable(s). OP mentioned ony one model. So, no question of blindly applying same trick to "both".
I don't get your point. Can you point out some of such problems? It will be a nice help.statdad said:No - exponential regression (the method you pointed out) and polynomial regression (the question posed by the OP) are not identical, and treating them as such causes problems.
Regression analysis is a statistical method used to quantify the relationship between two variables, typically referred to as the independent variable (x) and the dependent variable (y). It is used to determine how changes in the independent variable affect the dependent variable.
The purpose of using regression analysis in Excel is to find the best-fit line that describes the relationship between two data sets. This can help predict future values of the dependent variable based on changes in the independent variable.
To perform a regression analysis in Excel, you will need to have two data sets for the independent and dependent variables. Then, you can use the built-in "Data Analysis" tool to generate a regression equation and plot the data on a scatter plot.
The regression coefficient (C) represents the slope of the regression line, indicating how much the dependent variable changes for every unit change in the independent variable. The exponent (n) is the power to which the independent variable is raised, indicating the type of relationship between the variables (e.g. linear, quadratic, etc.).
The results of a regression analysis in Excel will include the regression equation, the coefficient of determination (R-squared), and the p-value. The regression equation can be used to predict future values of the dependent variable. The R-squared value indicates the strength of the relationship between the variables, with higher values indicating a better fit. The p-value is used to determine the significance of the relationship, with values less than 0.05 indicating a significant relationship.