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for my college project I conducted an experiment and gathered measurements of soil respiration over 90 day period. I am interested how much CO2 I'd get after those 90 days, therefore interpolated measurement data between sampling days and summed it all up to find out the amount in the end. Now I have a total number of CO2 emissions over this time period with 9 different treatment groups. What I'd like to find out is how to prove whether differences among these groups are statistically significant. Basically I am interested interested to find p-value. I thought of using ANOVA, however I do not have any raw data. I have only means, standard deviations, standard errors and sample size available. How would you suggest to evaluate this type of data?

Many thanks in advance.

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    $\begingroup$ Why can't you use ANOVA? The standard deviations gives you the variance within groups, and the mean of each group gives you the variance between groups $\endgroup$ – Hugh Dec 7 '16 at 13:52
  • $\begingroup$ I thought of doing that, but wasn't sure if I'm correct. Tried doing it in SPSS, but got a blank result page, so I thought the method must be wrong. I'll try to see if I did something wrong in the programme. Thanks! $\endgroup$ – iirisa Dec 7 '16 at 14:49
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    $\begingroup$ I think you have to calculate it manually, I'd be surprised if SPSS allowed you to input summary statistics and then calculate the F statistic $\endgroup$ – Hugh Dec 7 '16 at 15:26

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