Create README.md

Background and intro, plus an explanation/overview of each section included

README.md

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+# Module 5 Challenge: Analysis of Skin Cancer Drug Treatments in Mice
+The purpose of this challenge is to analyze the effectiveness of various drugs on reducing 
+the tumor size of a certain type of skin cancer in mice, with a focus on the drug Capomulin.
+The results are displayed in various graphs in order to visualize factors such as number of 
+tracked timepoints per drug, sex distribution, final tumor volume at the end of treatment for the 
+top four performing drugs, and mouse weight versus average tumor volume for the Capomulin treatment group.
+
+## Summary Statistics
+This section includes a summary table showing the following tumor metrics for each drug treatment:
+* mean tumor volume
+* median tumor volume
+* tumor volume variance
+* standard deviation of tumor volume
+* standard error of the mean of tumor volume
+
+## Bar/Pie Charts
+The bar charts created in this section both display the total number of timepoints for each drug treatment
+over the course of the study. One chart was created using the Pandas DataFrame.plot() method, while 
+the other was created using Matplotlib's pyplot methods. 
+
+## Quartiles, Outliers, and Boxplots
+In this section, the final tumor volume (that is, the volume of the tumor at the end of the 45 day treatment
+regimen) was calculated for the four most promising drugs: Capomulin, Ramicane, Infubinol, and Ceftamin.
+This data was plotted in a boxplot, with any potential outliers displayed. 
+
+## Line/Scatter Plots
+In this section, a line plot of tumor volume versus time point (over the course of the 45 day treatment regimen)
+was plotted for a single mouse with the Capomulin treatment group. The code is written such that each time
+it is run, a random mouse from the group is selected and its data displayed. 
+Next, a scatter plot was created that displays the mouse weight versus average observed tumor volume for 
+every mouse included in the Capomulin treatment group.
+
+## Correlation/Regression
+In this section, the correlation coefficient and linear regression model were calculated for mouse weight 
+versus average observed tumor volume for every mouse included in the Capomulin treatment group. The correlation
+coefficient was found to be 0.84 (strong positive correlation) and the linear regression model was
+plotted on the scatter plot created in the previous section.
+
+## Copyright
+Data generated by Mockaroo, LLCLinks to an external site., (2022). Realistic Data Generator. 
+Data for this dataset was generated by edX Boot Camps LLC, and is intended for educational purposes only.