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Hello Bobs
I ran an independant T test using SPSS and got T values of
Sitting - 42.346
Standing - 47.519
exercise - 41.610
(P values of 0.00, does this mean there is almost certainly a a rise in pulse across variables? i.e reject my null hypothesis)
Im not sure how to interpret this information. I had a look at the T tables but I wasn't sure which T.x I should be using. Could you give me any pointers?
Im pretty confused to be honest. What I really want to do is get a P value that allows me to reject my null hypothesis that there will be no change in pulse across my independent variables. How do you think this is best achieved using SPSS? Or have I already achieved this with my sig of 0.00?
Thank you for giving me the formula to achieve these tests, but my teachers want us to use SPSS and provide output data.
Many thanks
Max
Thanks! Yeah - smiely overkill! Sorry about that!
Hello Maths wizards and apprentices
My name is Max, I'm a Podiatry Student with a provisional interest in research. Unfortunately maths is one of these topics that I, like many others, have spent my life running away from. But you cant escape it! And it is gosh darn interesting.
I have been offered a summer job at the university acting as a research assistant to a PhD student looking a intrinsic foot muscle strength. I will have to learn a lot fast in order to keep up and be useful to my PhD boss. So I anticipate that I will be doing a great deal of posting with regards to statistics over the next few months.
Thanks for reading!
Max
Hello
I'm a podiatry student working on a simple data analysis assignment for class. I'm not 100% sure if this forum is cool with students asking for help with their homework - I know that the podiatry forums hate it! - so if I'm making a bit of a faux pas, then I'm very sorry about that and please ignore my post.
Otherwise here is my predicament:
We have to look at some data and determine whether pulse is affected by exercise.
I have a group of people in my sample (n=20) and 3 data sets - pulse when: sitting, standing and after running.
I want to get values for variability within the data sets, as the mean for each data set seems to go up as expected, but the actual data points are all over the shop. I want to get the variability values so I can justify investigating why the variability is so high and whether this variability could undermines my hypothesis - that exercise makes your pulse go up.
What would be the best test to use to determine the variability for each data set?
I think I have probably come across the answer online, but the shear variety and complexity of tests out there has got me stumped.
Can anyone give me any pointers?
N.B - most of my fellow students are working with very very simple values like mean and SD. Im keen to go a bit further as I have been offered a summer job at the uni working on a Phd research project and I really want to flex/build some stats muscle and I'm trying to use this assignment as a training ground. I really do like statistics, but I have a long way to go........
P.S nice selection of smileys here!
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