I need someone for my statistical analysis for my research......My topic is Comparative effects of Forest Dominant Trees on Soil Characteristics..........Is there anyone with statistical specialty .????
Dear Russel.... I haven't been collected my data... I am actually looking for someone who is expert in statistical analysis and I would like to share my work with him.... And point about the person helping me will be credited or not? the answer is I haven't enough pocket money to pay him "sincerely". but he will be among co author in my paper..........
For this type of study, I suggest you focus your reading on one statistical course called "Design of Experiments" or "Experimental Design". Get the book and read carefully. I can guide you on this but its better if you read the book first. Don't be upset if the book contains too much mathematical formula. If it is too difficult to grab - then you get this book "introduction to Design of Experiments"
I agree with the answers above. It is important for you to know what your data means. Internet has a lot of resources to achieve this. I suggest you to register in Coursera.org and learn some basics on statistics (https://www.coursera.org/courses?query=statistics). You can also look for someone which helps you, but from my point of view, if its your research, you should be the first understanding your results, because you have to explain them and tell the others what do they mean.
If you are a scientist, then start changing this reality. Otherwise, go and do your buisiness but do not contaminate science...
I know this "reality" very well. Unfortunately. But more and more reviewers start asking good questions about the data analysis. It does in fact become more and more important (although still on a relatively low level, but it's growing). Yesterday I was talking to a PhD candidate who submitted his thesis. The thesis came back with the question why he analyzed the data the way he did. It was obviousely a quite wrong analysis, because the main research questions was not answered by this analysis, and the reviewer correctly pointed this out. The candidate was (he is) completely lost now, because he had no other reason to do this analysis this way because (1) all others do it this way, (2) he was really told to do it this way, (3) in many published papers (including his own!) it was done this way, and, finally (4) he has no idea about data analysis (and statistical thinking).
He is in a very bad situation, there is actually no good solution. He can either withdraw his publications or his thesis. Both alternatives are quite ruinious...
Such situations become more and more frequent. It is sad that the students have to suffer most (from the bad supervisors telling them to do "stupid" things, and from the curriculum teaching stats in a wrong way, from reviewers who still insist on bad analyses, and - also! - from the disability of teachers and institutions and universities to recognize that [good] empirical science is not possible without scientific and statistical thinking and to take appropriate actions), but changes always happen over generations. The PhDs who have encountered such problems may be more careful in instructin their students when they will be supervisors (well, not all, but some at least. Hopefully).
Sampath pointed out a very important issue which has in fact become a regular practice even in pure Statistics not to talk about allied subjects in some universities. There are examples plenty of them. Many of these so called Ph. D. holders are now supervisors themselves and will produce even inferior Ph. D.s . This has become more because of the so called API marking system which only look at the quantity sans quality.
In some universities, each Ph.D. committee of dissertations with quantitative portions must have one statistics professor as a committee member. This is the way to go to educate everybody else on how to correctly use statistics. Modeling and checking model assumptions is very important. Software packages will not do the modeling for anyone.