# Module 2 Organizing, Visualizing, and Describing Data

Lesson 1: Categorizing, Organizing, Summarizing, and Visualizing Data

LOS
Identify and compare data types.
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- easily organized and presented as arrays of variables or dimensional data tables

- do not follow conventional organization approaches. EX: filings with regulators, posts in social media, other types of non-data financial news, management earnings calls, and analyst presentations. Words or images that are difficult to logically categorize, manipulate, or use in financial modeling.
- describes the number of observations

- divides the number in each group or interval by the total number of observations to provide a normalized comparison (i.e., a percentage).

( look at picture will be faster) Histograms

Frequency Polygon

Cumulative Frequency Distribution ( tend to flatten out when returns are extremely negative or extremely positive.)

Bar chart ( like a histogram, but for categorical rather than numerical data)

Grouped bar chart (known as a clustered bar chart)
vs
Stacked bar chart

Tree map ( consists of colored rectangles that represent categories or intervals of data, identify subgroups )

Word cloud ( represents textual data with the value of observations represented by the size of the words and the category or the sentiment represented by the color of the words, It's for unstructured data)

Bubble chart (a frequency polygon representing multi-dimensional data)

scatter plot ( common in a linear regression)

heat map ( assigns different colors indicating the magnitude of the variable Lesson 2 Measures of Central Tendency, Quantiles, and Dispersion

LOS: Calculate and interpret measures of central tendency.

LOS: Evaluate alternative definitions of mean to address an investment problem.

LOS: Calculate quantiles and interpret related visualizations.

LOS: Calculate and interpret measures of dispersion.

LOS: Calculate and interpret target downside deviation.
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