R-Studio Independent Variable Project
Budget: $30 – $250 USD
project
Preparations:
1) Choose a topic and a research question: Are Y and X are correlated?
- Y: Dependent variable
- X: Independent variable of interest
2) Choose two control variables (they are also independent variables)
3) Collect data for your variables
- You need at least 30 observations
- Your dependent variable must be quantitative
- From you three independent variables, one of them must be binary.
In your r-script:
1) Describe your research question and why you think X & Y are correlated.
2) Discuss your variables. Use figures and tables to examine your variables and possible correlation between your independent variable of interest and your dependent variable (you can use tables, box-plots, scatterplots, and so on here). It depends on your research question and variables.
3) Define your model & run a linear regression
4) Discuss your results. In this section you must discuss and interpret your coefficients.
5) Draw some conclusions based on your results
6) Discuss how this research can be improved for future studies
To submit:
- Create a zip file that includes your R-script and dataset (it must have the dataset)
- Upload the zip file
Preparations:
1) Choose a topic and a research question: Are Y and X are correlated?
- Y: Dependent variable
- X: Independent variable of interest
2) Choose two control variables (they are also independent variables)
3) Collect data for your variables
- You need at least 30 observations
- Your dependent variable must be quantitative
- From you three independent variables, one of them must be binary.
In your r-script:
1) Describe your research question and why you think X & Y are correlated.
2) Discuss your variables. Use figures and tables to examine your variables and possible correlation between your independent variable of interest and your dependent variable (you can use tables, box-plots, scatterplots, and so on here). It depends on your research question and variables.
3) Define your model & run a linear regression
4) Discuss your results. In this section you must discuss and interpret your coefficients.
5) Draw some conclusions based on your results
6) Discuss how this research can be improved for future studies
To submit:
- Create a zip file that includes your R-script and dataset (it must have the dataset)
- Upload the zip file