1. KB
    2 years & 1 day ago

    Thank you! this helps so much.

    Reply
  2. Habu Haruna
    2 years & 4 months ago

    The article was helpful

    Reply
  3. Rich Joseph
    2 years & 4 months ago

    Hi Riya,

    I read your post on the interpretation of regression results and I really learnt a lot from it.
    I commend you for the good work.

    I ‘d like to be under your mentorship

    Reply
  4. JOHN MANOHAR
    2 years & 5 months ago

    Ms. RIYA JAIN:

    Given below is a Regression Table arrived at after analyzing the data. The objective is to discuss the Perceptions and Expectations of online retail traders regarding the Service Quality from the e-broking firms.

    I am at a loss as to how interpret and conclude the findings.
    Table 5.2.37
    Regression Summary (N=384)

    Variables Regression Coefficients Std. Error t R2
    (Constant) 1.554 .145 10.735 .323
    Efficiency – X1. .002 .072 .028
    Fulfilment – X2. .011 .071 .150
    System Availability – X3. .325 .094 3.456
    Privacy – X4. .370 .060 6.162
    Responsiveness – X5. .120 .035 3.402
    Compensation – X6. -.448 .063 -7.078
    Contact – X7. 1.554 .145 10.735

    Could you please help me with this?

    Thanks in anticipation.

    Reply
  5. HABILA NUHU
    2 years & 10 months ago

    I find this article very helpful. now i know how to interpret thanks

    Reply
  6. Akibu
    2 years & 10 months ago

    Wonderful interpretation.

    Reply
  7. Aragieamanu
    2 years & 10 months ago

    Thanks

    Reply
  8. Sewwandi Rathnayaka
    2 years & 11 months ago

    Please advice me, how to interpret below mentioned my results of Regression Analysis ??

    Model (Variable) Unstandardized Coefficients Standardized Coefficients

    B Std. Error Beta t Sig.
    (Constant) 0.755 0.173 4.373 0.000
    Workload and Workplace Related Stress -0.04 0.202 -0.035 -0.171 0.865
    Organization Related Stress -0.12 0.119 -0.214 -0.975 0.338
    Working Time Related Stress 0.139 0.127 0.220 1.095 0.283

    Model Summary

    R R Square Adjusted R Square Std. The error of the Estimate F Sig.

    0.246 0.06 -0.04 0.39117 0.60 0.62

    Reply
  9. Bernard
    3 years & 1 month ago

    Hello,

    I find this article very insightful and helpful but I would want to find out what kind of adjustments can be made should your data produce R-values and R-square values less than the standard limit.
    Thanks

    Reply
  10. Noor Dani
    3 years & 2 months ago

    Dear Riya and Priya,

    I have been searching high n low for F-Ratio interpretation. Now I know a value greater than 1 for the F- ratio yield efficient model. Thank you so much.

    Reply