I am a researcher investigating the visual properties and pollination success in flowers. I have a large dataset with 21 explanatory variables (mix of categorical, continuous and dates) for 3 continuous outcome variables and their SDs.
For each flower measured, the outcome variables have been obtained for different regions of the flower, i.e. 1 flower has 20 descriptive categories, 1 category separating the measurements by region of the flower, and the 3 measured visual variables for each region.
I am trying to determine which explanatory variables best predict / group the outcome variables, so I can determine what hypotheses to pursue in future field work. I have identified Multiple Factor Analysis as an appropriate method to do this, though I am open to suggestions.
I would like for someone to help me achieve this in R, who would be happy to provide me with the code afterwards in addition to some graphs. I don't need any reports written about the analysis.
I'd be happy to give any additional details that would help to obtain a quote for this work please. I have included a subset of the data with 4 flowers measured. Thanks!
Hi I have a masters degree in statistics for data science from Le CNAM Paris and I have R programming certification I'll be glad to help you achieve the task Waiting to hear from you Regards
Bu iş için 15 freelancer ortalamada £129 teklif veriyor
Hello sir/ma, I'm interested in taking this task up for you. I have a Master's degree in Economics and Statistics with 7years of professional experience working as a Data Analyst (in the field of Statistics). As a prof Daha Fazla