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Mathematics 10 Online
OpenStudy (anonymous):

I've done a survey for a research paper and I don't know how to "run the stats" on the results. Does someone have an example?

OpenStudy (amistre64):

whats your data and what stats do you need?

OpenStudy (amistre64):

are the results to be a sample of the overall population or is this just to be considered as the population you collected?

OpenStudy (anonymous):

i sampled students from 5 different disciplines to find out how they work with social media in school

OpenStudy (anonymous):

I wanted to see if there was difference between industrial design students and accounting students

OpenStudy (anonymous):

but i have no foundation in stats

OpenStudy (amistre64):

well, without any numbers to crunch and a clear objective; its a hopeless endeavor.

OpenStudy (amistre64):

the mean is the most common statistic; but what is it we are comparing? how large is the data set? etc etc ...

OpenStudy (amistre64):

are the samples random samples or simple random samples? i still aint figured out how to tell the difference :)

OpenStudy (amistre64):

what is your null hypothesis? what is your confidence level? stuff like that. Without a clear objective ... just running the numbers is futile

OpenStudy (anonymous):

my hypothesis is that industrial design students will find more value in collaborative learning than other students-- pulled sample from approx 2000 students over 5 different disciplines, of which 300 responded.

OpenStudy (anonymous):

one of those disciplines is industrial design, the rest are non-design students

OpenStudy (amistre64):

hmmm ..... the manner in which the results were obtained means that the results are only suitable for the population you were able to get ..

OpenStudy (amistre64):

need to redress the hypothesis so that it can be quantified too. Hard to test the hypothesis on a vague value cause there is no way to determine a cutoff point.

OpenStudy (amistre64):

for example: more than 95% of industrial design students find more value in collaborative learning than other students. H0 = 95% H1 > 95% is testable

OpenStudy (amistre64):

If the stats fall in the H1 part, the hypothesis is rejected if they fall within the H0 part, the hypothesis might be good or bad, but at least its got some degree of non rejectablity :)

OpenStudy (anonymous):

oh, i see what you mean. Sure, that makes sense

OpenStudy (anonymous):

It was just the manner of how to present it that I needed to clarify-- I'm so used to qualitative data!

OpenStudy (anonymous):

really regretting not taking stats :)

OpenStudy (amistre64):

im just wrapping up elementary stats this term :)

OpenStudy (anonymous):

thanks for your help-- this is a good start. going to go watch some tutorial vids :)

OpenStudy (amistre64):

good luck ;)

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