R Code for Hypothesis and Regression Analysis

I'm looking for an expert in R programming, with a strong foundation in hypothesis testing and regression analysis. For this project, you will work with numerical and time-series data. It involves generating code for running a regression with 4 explanatory and one dependent variable. The analysis is for a thesis, and although we have some knowledge within r and statistical programming we encountered some issues and are therefore looking for help.

The tests considered relevant:
- ADF and PP test, where the Phillips-Perron is to complement ADF´s inability to check for autocorrelation and heteroskedasticity in the data
- Determining the correct number of lags for the regression
- cointegration tests.
- Panel Data Analysis.

Creating a regression - explaining why this is the best suited for the model (only a couple of sentences needed)

Any other tests considered relevant for generating a sufficient regression.


Key Responsibilities:
- Develop R code to perform hypothesis testing and regression analysis
- careful explanation for each step in the code
- Assess the dataset and determine whether preprocessing or cleaning is required

Preferable skills include:
- Experience in hypothesis testing and regression analysis
- Skill in dealing with numerical and time series data
- Competence in data cleaning

Please note that the current state of the dataset is uncertain, and potential cleaning may be needed. If you're familiar with managing and fixing potential data issues, this would be perfect for you.

I'm looking forward to work with someone who can succinctly communicate their findings in a clear and straightforward manner.