How do I answer this question? data set is too large to upload, Show me what direction I need to take in order to solve:

Question: You are tasked with analysing the results of an experiment testing the efficacy of two new chermotherapy drugs in comparison to the drug currently marketed by your company. The response variable is the change in tumor size measured in milligrams. The explanatory variables are the different drug treatments: the currently used drug (control, labelled C), new drug A, and new drug B in two doses, low (B_L) and high (B_H). Your goal is to determine which of the drugs, if any, have a significant effect on the response variable, and in which direction, and whether either of the new drugs are strong candidates for potential use (after further testing of course!), while answering/doing the following: 1) What are the assumptions of the statistical test(s) that could be used to analyze this data and are those assumptions met for your dataset? Include one graph in your answer with a brief explanation of what the graph demonstrates, as well as the results of two sets of statistical analyses with single-sentence conclusions with respect to the null hypotheses. 2) Perform a statistical analysis based on the results of 1). Note: you should ignore data transformations for the purposes of this assignment. Include your results in a display table and provide a single-sentence conclusion with respect to the null hypothesis and a conclusion with respect to the scientific hypothesis (i.e., what can be concluded about the effect of the explanatory variable on the response variable?). 3) Based on the results of 1) and 2) perform an additional statistical analysis, as appropriate. Include your results in a display table, along with a single-sentence conclusion with respect to the null hypothesis and a conclusion with respect to the scientific hypothesis, including your determination on which of the new drugs is a candidate for potential use, if any. 4) Display your data and results from 3) in an appropriately labelled graph.