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# Module 4: Outline
1. Introduction to Data and Scientific Datasets
a. What is scientfic data
b. Data Processing flow work
c. Intro to Pandas
d. Manipulating data frames
e. Problem: Create a daraframe from Numpy arrays
2. Interpreting Data
a. Understanding your data
b. Purpose
c. Composition
d. Color
e. Problem 1: Composing or fixing a plot
f. Data don't lie
g. Problem 2: Misleading plots
3. Importing, Exporting and Managing Data
a. File types
b. Importing spreadsheets with pandas
c. Handling header, units and metadata
d. Writing and editing data in pandas
e. Problem: Importing time stamped data
4. Statistical Analysis
a. Engineering Models
b. Statistics Review
c. Statistics function in python (Numpy and Pandas describe)
d. Statistical Distributions
e. Spectrocopy (basics)
f. Problem: Statistical tools in Spectroscopy readings
5. Statistical Analysis
a. Linear Square Regression and Line of Best Fit
b. Linear
c. Exponential and Power functions
d. Polynomial**m 2:** From the DataFrame, add a
e. Using scipy
f. How well did we do? (R and R^2)
g. Extrapolation
h. Moving average
6. Data Filtering and Signal Processing
7. Data Visualization and Presentation
a. Problem: Using pandas to plot spectroscopy data from raw data.
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