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# linear regression and fF-test

I have three data points. (110,1.95), (120, 3.03), and (130, 4.75) Y-values are observed deltas of means and X-values represent temperature settings. After plotting and running a linear regression I get an R$$^2$$ value 0.983 (Adjusted R$$^2$$ = 0.966). An F-statistic of 57.42 with a p-value of 0.08.

Would the observation that as temperature increases so do the predicted Y-value, be valid? Am I confusing myself by looking at the fF-test? withWith the p-value > 0.05?

I have checked Whats the relationship between $R^2$ and F-Test?

Thanks

In case it matters --- Formatters—For linear regression and OLS regression results I used Python scipy.stats.linregress(x,y) and statsmodels.formula.api

# linear regression and f-test

I have three data points. (110,1.95), (120, 3.03), and (130, 4.75) Y-values are observed deltas of means and X-values represent temperature settings. After plotting and running a linear regression I get an R$$^2$$ value 0.983 (Adjusted R$$^2$$ = 0.966). An F-statistic of 57.42 with a p-value of 0.08.

Would the observation that as temperature increases so do the predicted Y-value, be valid? Am I confusing myself by looking at the f-test? with the p-value > 0.05?

I have checked Whats the relationship between $R^2$ and F-Test?

Thanks

In case it matters --- For linear regression and OLS regression results I used Python scipy.stats.linregress(x,y) and statsmodels.formula.api

# linear regression and F-test

I have three data points. (110,1.95), (120, 3.03), and (130, 4.75) Y-values are observed deltas of means and X-values represent temperature settings. After plotting and running a linear regression I get an R$$^2$$ value 0.983 (Adjusted R$$^2$$ = 0.966). An F-statistic of 57.42 with a p-value of 0.08.

Would the observation that as temperature increases so do the predicted Y-value, be valid? Am I confusing myself by looking at the F-test? With the p-value > 0.05?

I have checked Whats the relationship between $R^2$ and F-Test?

In case it matters—For linear regression and OLS regression results I used Python scipy.stats.linregress(x,y) and statsmodels.formula.api

1

# linear regression and f-test

I have three data points. (110,1.95), (120, 3.03), and (130, 4.75) Y-values are observed deltas of means and X-values represent temperature settings. After plotting and running a linear regression I get an R$$^2$$ value 0.983 (Adjusted R$$^2$$ = 0.966). An F-statistic of 57.42 with a p-value of 0.08.

Would the observation that as temperature increases so do the predicted Y-value, be valid? Am I confusing myself by looking at the f-test? with the p-value > 0.05?

I have checked Whats the relationship between $R^2$ and F-Test?