0
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Call:
lm(formula = formal_engaged_replaced ~ setting_interest + setting_trust + 
    setting_contact + setting_confidence + setting_visibility + 
    network_close_network + network_help_neighbour + network_help_orgs + 
    personal_sex + poverty_replaced + personal_education, data = train_model)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.6084 -0.3168 -0.1750  0.4730  0.9894 

Coefficients:
                        Estimate Std. Error t value Pr(>|t|)    
(Intercept)             0.694967   0.172963   4.018 8.15e-05 ***
setting_interest        0.082989   0.036994   2.243   0.0259 *  
setting_trust          -0.095590   0.039447  -2.423   0.0162 *  
setting_contact         0.006969   0.040477   0.172   0.8635    
setting_confidence      0.023480   0.041886   0.561   0.5757    
setting_visibility      0.090994   0.040536   2.245   0.0258 *  
network_close_network   0.001323   0.004591   0.288   0.7734    
network_help_neighbour -0.008214   0.030320  -0.271   0.7867    
network_help_orgs       0.032154   0.032971   0.975   0.3306    
personal_sex            0.016613   0.059559   0.279   0.7806    
poverty_replaced        0.017542   0.034989   0.501   0.6167    
personal_education      0.035840   0.020845   1.719   0.0870 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4294 on 212 degrees of freedom
Multiple R-squared:   0.11, Adjusted R-squared:  0.06385 
F-statistic: 2.383 on 11 and 212 DF,  p-value: 0.008439

I already performed wilcox test on this dataset for the hypothesis test, is it necessary to check the assumptions for the regression, just to check dependent variable has significant effect from which variables?

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5
  • 1
    $\begingroup$ If you don't care about the results and won't be communicating them to anybody, then no, you don't need to check. $\endgroup$
    – whuber ♦
    Jan 22 at 17:55
  • 2
    $\begingroup$ What assumptions, specifically, do you think the regression requires? There are some common misconceptions about that... $\endgroup$
    – jbowman
    Jan 22 at 18:16
  • 1
    $\begingroup$ And for what reason do you want to check the assumptions (or even what reasons you want to run the regression at all)? Depending on what you want to do, some assumptions are not so important. In particular, an assumption about normal errors has to do with coefficient t-stats, confidence intervals, standard errors, and p-values. If those are not of interest to you (maybe they are, but sometimes they aren’t), then such as assumption is less important. $\endgroup$
    – Dave
    Jan 22 at 18:31
  • $\begingroup$ Advice from a related CV thread: When to check model assumptions $\endgroup$
    – dipetkov
    Jan 22 at 18:50
  • 1
    $\begingroup$ In practice, all or almost all assumptions (when you need them at all) will be strictly false... you can't even know when an assumption does hold, it's an assumption, what matters for something that relies on some set of assumptions is how wrong, in what way and how consequential that might be. $\,$ In the words of George Box: "Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful." $\endgroup$
    – Glen_b
    Jan 22 at 22:55

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