title: Extracting t-stat p values from lm in R
body: <p>I have run a regression model in R using the lm function. The resulting ANOVA table gives me the F-value for each coefficient (which doesnt really make sense to me). What I would like to know is the t-stat for each coefficient and its corresponding p-value. How do I get this? Is it stored by the function or does it require additional computation?</p>
  
  <p>Here is the code and output:</p>
  
  <pre><code>library(lubridate)
  library(RCurl)
  library(plyr)
  
  [in] fit &lt;- lm(btc_close ~ vix_close + gold_close + eth_close, data = all_dat)
  
  # Other useful functions 
  coefficients(fit) # model coefficients
  confint(fit, level=0.95) # CIs for model parameters 
  anova(fit) # anova table 
  
  [out]
  Analysis of Variance Table
  
  Response: btc_close
             Df   Sum Sq  Mean Sq  F value Pr(&gt;F)    
  vix_close   1 20911897 20911897 280.1788 &lt;2e-16 ***
  gold_close  1    91902    91902   1.2313 0.2698    
  eth_close   1 42716393 42716393 572.3168 &lt;2e-16 ***
  Residuals  99  7389130    74638                    
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  </code></pre>
  
  <p>If my statistics knowledge serves me correctly, these f-values are meaningless. Theoretically, I should receive an F-value for the model and a T-value for each coefficient. </p>