This is the question I need help on. I need help on question 2-6 please.

Find the best-fit distribution using Maximum Likelihood Estimation (MLE).

1. Import the data from the file 'SomeNumbers.csv'.
2. Describe the data: state the size and shape of the dataset and the nature of the numbers enclosed.
3. Plot a normalised histogram of the data.
4. These data come from a Negative Binomial distribution. A function needs to be written so that it computes the log-likelihood. HINT: You can let log(0) = 0 if required.
5. The Negative Binomial distribution has two parameters, N and p. Using your code from part 4, compute the values of log-likelihood for values of N in the range [10-60] and p in the range [0-1] (e.g. use 50 values).
6. Plot your results as a two-dimensional plot with the value of log-likelihood as the colour (or equivalently, make a contour or three dimensional plot). Comment on your results.
7. Compute the maximum of the log-likelihood and find the best-fit values of N and p.
8. Create a plot of the best-fit distribution on top of the histogram from part 3. Comment on your results.

The data in the excel are just positive numbers.