Ordinal logistic regression and its interpretation

I fitted an ordinal logistic regression but I'm unable to interpret the coefficients. Can anyone assist in this regard? Here is the output generated:

Call:
polr(formula = factor(grade) ~ factor(Month) + Day, data = myData,
Hess = TRUE)

Coefficients:
Value Std. Error t value
factor(Month)4 1.405114    0.51547  2.7259
Day            0.007672    0.01944  0.3947

Intercepts:
Value   Std. Error t value
1|2 -0.6785  0.7019    -0.9667
2|3  1.6767  0.7162     2.3412

Residual Deviance: 333.602
AIC: 341.602


1 = good
2 = very good
3 = excellent

Month is factored:

3 = March
4 = April

The grade is the response while month and day are my explanatory variables.

• This might help you: Negative coefficient in ordered logistic regression. – gung Oct 21 '15 at 0:03
• I don't get you. can you explain please? – liz Oct 21 '15 at 0:43
• There's a lot of information at the link that can help you interpret OLR models. Can you be more specific about what you need to know? Eg, do you know what a standard error is? – gung Oct 21 '15 at 1:07
• Yes, I know what standard error is which is the standard deviation divided by the square root of n. My question is "How do i interpret the coefficient values for Day and Month with respect to the response variable which in this case is the grade? – liz Oct 21 '15 at 2:04
• the standard error you reported in your question is not the standard deviation divivded by the square root of n. – Maarten Buis Oct 21 '15 at 8:54