I was collected my ten scale level data from from infected and control(non inoculated) by plant pathogen. Therefore, which statistical tools is appropriate for my data analysis?
Hard to say without knowing a bit more about which of your variables are independent and dependent. But it sounds like you possible require some form of MANOVA test. SPSS software will easily handle this - takes a little while to get used to but very quick after that.
Your last question (... which statistical tools is appropriate for my data analysis?) is more important than the first one (software).
In order to compare the averages of two groups, the more commonly used tests are: the Student t-test, appropriated if you have adherence to the gaussian distribution, or Wilcoxon Rank Sum Test (or Mann Whitney U Test) appropriated if the assumption of normality can't be accepted.
The nature of the data (ordinal scale) points to a non-parametric option (Wilcoxon) but un expert analyst can take another decision with basis in prelliminary analysis of your data.
If you had motive to apply the non-parametric test see the link
Thank you Marcelo Correa Alves for your recommendation!
As i have tried to explain my question, i am collected my data from infected pepper by scaling 0= no symptom of infection; 2= little symptom and....10= died plant by infection. Therefore, my question is which statistical tool is more appropriate to analysis my data?
As i have tried to explain my question, i am collected my data from infected pepper by scaling 0= no symptom of infection; 2= little symptom and....10= died plant by infection. Therefore, my question is which statistical tool is more appropriate to analysis my data?
As your measurement scale indicates the interval scale, so it is better to go for parametric tests like t-test and others, I am strongly agreed with David L Morgan