The Lending Club is a lending company based on San Franscisco, CA.

Analyze This Big Amount of Information
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Analyze This Big Amount of Information
1 Start by making initial observations of the data. What types of variables are present? Is there anything that catches your eye?
The types of variables present in the data provided are the following with their respective examples:
* Quantitative-numerical, i.e., continuous and discrete. E.g. loan amount, funded amount, funded amount inventory, term, installment, annual income, etc.
* Qualitative-categorical i.e. nominal, ordinal, ratio and interval. E.g. grade, subgrade, employment title, sub-grade, home ownership, loan status, address state etc.
Surprisingly, the variables present in the data can be sub-grouped into either continuous or discrete if it’s numerical and nominal, ordinal, ratio, or interval if it’s qualitative. Conclusively, the data has all variables.
2 Use at least two ways to summarize the qualitative data present in the data set with frequency distributions and the various graphs/charts we have used in the class for Chapter 2.
Two ways to summarize the qualitative data are by use of frequency bar graphs and a regular pie chart. Below is a pie chart and bar plot of the variable ‘home ownership’ in the data.
3 Do the same thing with the quantitative data present. These four ways should be different aspects from the data set. Interpret your results.
To summarize, the quantitative data bar plots and histograms are used. Below are a bar plot and histogram of the ‘total recovered principal’ variable.
4 Pick two of the above graphs you chose and describe the shape of those distributions.
The two graphs, a histogram of total recovered principle variable and a bar plot of home proprietorship, can be used to describe the shape of a distribution. The histogram shows a positively skewed or right-skewed distribution similar to the bar plot’s non-symmetric distribution, which is negatively skewed.
* Why did you use certain graphs you did?
From the two charts, one can tell the frequency on the histogram’s y-axis and the height of the bars of the bar plot that show how each type of data is spread across the entire datasets.
* Are there any benefits over the other?
Additionally, bar plots and histograms can visually elaborate on measures that describe a distribution, i.e. mode, minimum, maximum, etc. as compared to a pie chart.
5 Now I want you to take two variables you think might be related. Create a scatterplot. Find the covariance, correlation, and interpret the results.
I chose the funded amount inventory and total payment inventory.
Covariance= 22432687
Correlation= 0.8190714
The covariance of both va...