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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?

and If the f-test is insignificant but coefficients are significant, can I use it?

so if your comment is to refer me to these answers please add something to help me see the connection.

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?

and If the f-test is insignificant but coefficients are significant, can I use it?

so if your comment is to refer me to these answers please add something to help me see the connection.

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?

and If the f-test is insignificant but coefficients are significant, can I use it?

so if your comment is to refer me to these answers please add something to help me see the connection.

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

1
source | link

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?

and If the f-test is insignificant but coefficients are significant, can I use it?

so if your comment is to refer me to these answers please add something to help me see the connection.

Thanks

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