Standard error of the mean (SEM) represents the accuracy of the mean. Here's my question/doubt. 
    Does higher the SEM mean higher the accuracy of the mean?
    To be more precise, what indicates more accuracy of the mean? sem = 3.5 or sem = 1.5?

This may seem odd but it keeps on pestering me for a very long time. Thank you in advance.

This is an alternative answer: optimizers in statistical packages usually work by minimizing the result of a function. If your function gives the likelihood value first it's more convenient to use logarithm in order to decrease the value returned by likelihood function. Then, since the log likelihood and likelihood function have the same increasing or decreasing trend, you can minimize the negative log likelihood in order to actually perform the maximum likelihood estimate of the function you are testing. See for example the nlminb function in R here