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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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