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Editorial Team
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Asked: 2026-05-23T03:52:45+00:00

I have a sample data range that has four categories, foo | bar |

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I have a sample data range that has four categories,

foo   | bar |  bizz| buzz
---------------------------
163     345   456   2435
232     234   457   2435
123     346   234   3673

Foo is the dependant variable, bar, bizz and buzz are independant variables. I’ve went to Data Analysis => Regression => picked those columns as appropriate, gotten all of the regression statistics and some plots that represent it. How do I find the formula that it used so that I can use it in my predictions in an application?

SUMMARY OUTPUT                              

Regression Statistics                               
Multiple R  0.462484844                         
R Square    0.213892231                         
Adjusted R Square   0.212161986                         
Standard Error  2991.441979                         
Observations    1367                            

ANOVA                               
    df  SS  MS  F   Significance F          
Regression  3   3318714896  1106238299  123.6196536 8.06738E-71         
Residual    1363    12197112332 8948725.116                 
Total   1366    15515827228                     

    Coefficients    Standard Error  t Stat  P-value Lower 95%   Upper 95%   Lower 95.0% Upper 95.0%
Intercept   703.0478619 126.1475776 5.5732173   3.01028E-08 455.5834102 950.5123135 455.5834102 950.5123135
Bar 41.53512531 2.493716675 16.65591193 7.6937E-57  36.64318651 46.42706411 36.64318651 46.42706411
Bizz    1.96479128  0.361015402 5.442402932 6.22595E-08 1.256585224 2.672997336 1.256585224 2.672997336
Buzz    16.77200247 5.419776635 3.094592933 0.002010941 6.139994479 27.40401046 6.139994479 27.40401046



RESIDUAL OUTPUT                 PROBABILITY OUTPUT          

Observation Predicted foo   Residuals   Standard Residuals      Percentile  foo     
1   6780.632281 34894.36772 11.67756172     0.036576445 63      
2   6722.069851 28513.93015 9.542318743     0.109729334 63      
3   3382.925842 21471.07416 7.185394378     0.182882224 63
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1 Answer

  1. Editorial Team

    Oh hey, my stats class looks 98% less useless now.

    According to that output,
    foo = 703.0478619 + 41.53512531 * bar + 1.96479128 * bizz + 16.77200247 * buzz

    You can see these values where it lists the coefficients/standard errors for Intercept, Bar, Bizz, and Buzz.

    Should probably note that the r squared value is extremely low, which (if I recall correctly) means that the variance in foo is not well explained by the independent variables.

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