like a guide especially with putting the score for my survey.
*my survey will measure knowledge level for the disease population
Moreover, then which tool should I use?
My study is a cross-sectional quantitative
In my opinion , first thing is to understand your sincerity and regularity towards the particular goal, rest will be straight forward.
Moreover, the knowledge /hold on statistics plays significant role, so you must repeat them again and again... till you get better guidance.
Regards
Application of any statistical test solely depends on the objectives/design/hypotheses of the study.
Imran Anwar Study Design:
The research will be descriptive cross-sectional study design using survey
Well in that case, you can apply descriptive statistics for exploratory insights. Moreover, for checking mean differences across variables through demographic properties of the respondents, you can use t-test or ANOVA.
Better you can start with STATA or EVIEWS, but STATA would be more convenient for cross sectional data
In my opinion , first thing is to understand your sincerity and regularity towards the particular goal, rest will be straight forward.
Moreover, the knowledge /hold on statistics plays significant role, so you must repeat them again and again... till you get better guidance.
Regards
At first, you need to learn theoretical aspect of it. Therefore, you can execute and interpret it suitably.
I agree with Imran Anwar , and the statistical software I would recommend is Stata
I encourage my students to write your research questions in a simple regression equation. This means, students must define dependent variable, independent variables, and other demographic variables. This step can be done as students do their own literature review on the topic of interest (e.g., knowledge level of certain target population). After this step, students will obtain data sets. It is discouraged to collect your own data unless your thesis committee have agreed to guide you. Once data set is obtained, you would use some sort of statistical packages to test your hypothesis. There are many statistical packages you can use - some are free and some are not. Some universities have system-wide license for staffs and students, so ask your school's librarian. You may need to do further data manipulations prior to running any kind of analysis. This includes, cleaning, transforming, and imputing data. After you run your analysis, you would make interpretation. If you are not comfortable with making interpretation, I suggest you would arrange a meeting with faculty members of your institution who can give you further guidance. Good luck.
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