The project description should be carefully studied before bidding.
Data is confidential so details will be shared after awarding. However similar data is attached.
in Summary, we have three independent dimensions(categories) each one has a number of parameters, the parameters and the dimensions are not equally weighted.
the answers to the survey questions are from all types(yes or no, 1 to 5 scale, a matrix of answers, choosing many answers ..etc)
The project would have 3 milestones, we need the following:
1) coding the txt answers to numerical to start the analysis.
2) S.D and Mean for all questions to be provided on a dashboard
3) S.D and Mean for the three Major categories in the survey.
4) Internal consistency to be provided for each Category(Cronbach's alpha)
6) Identify the underlying parameters and recalculate the Cronbach's alpha after elimination
1)To find the best fit model for the data based on the data distribution, the correlation between all parameters, the significance of each parameter and internal consistency (Poisson, negative binomial or multinomial or multiple regression...etc)
2)run all the statistics checks like persons Shi square..G-Test, T-test MANCOVA, ACOVA Probit, Logit, Multinomial Logit, ..etc
3)compare the results and recommend the best model and create a prediction equation for the dependent factor having all the constant coefficients.
1) to write up a report describing all the work done and create dashboards for the presentation.
about 2000 words on the analysis - plagiarism free.
introduction and illustration for each model.
• show the significance of each model and how this model is good and what are the bad points of this model.
• show the 10% significance predictors and the 5% significance predictors of each model.
• shows the equation of each model and when applied on our data what would be the constant values for the coefficients.
• lastly, the report from the comparison of the models should state the best fit model for our data.