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Statistics Primer

→ Descriptive statistics

  • Discrete Data
  • Sample Distributions for Continuous Data
  • 5 Basic Descriptive Statistics for Continuous data
  • Outliers and Box plots
  • Comparing Data Sets
  • Measures of Center
  • Measures of Scale or Noise
  • Relation Ship between Variables
    1. Linear Models
      Residual Analysis
      Measures of relationships

→ Probability

  • Probabilities
  • Relative Frequency
  • Determination of Probabilities
  • Independence

→ Resampling

→ Discrete Populations(Probability Models)

  • Random Variables
  • Discrete Populations (Probability Models)
  • Parameters
  • Binomial Probability Model
  • Poisson Probability Model

→ Continuous Probability Models

  • Uniform probability model
  • Parameters
  • Normal Distribution
  • Normal Quintiles
  • Empirical Rule

→ Central Limit Theorem

  • Probability Examples
  • Central Limit Theorem

→ Confidence Intervals

  • Confidence Intervals for Means
  • Confidence Intervals for proportions
  • Confidence Intervals Based on Resampling

→Tests of Hypotheses

  • Testing Procedure
  • Wilcoxon
  • Wilcoxon: Other Alternatives

→Estimation of Effect : Two Independent Samples

  • Estimation and Confidence Interval Based on the Wilcoxon
  • Estimation and Confidence Interval Based on Means and Medians
  • Difference between proportions

→Design of Experiments

  • Completely Randomized designs
  • Randomized Paired Design
  • Signed-Rank Wilcoxon
  • Difference Between Proportions: Dependent samples

→Regression : Second Pass

  • Regression Experimental Designs
  • Observational studies

Python Primer

→Installation & IDE Basics

  • Installation anaconda
  • Working with SPYDER IDE
  • Working with Jupiter Note Book
  • Using the command History
  • Interacting With the Operating System
  • Software Development tools

→Numpy Basics: Arrays and Vectorized Computation

  • The Numpy ndarray
  • Universal Functions: Fast Element-wise Array Functions
  • Data Processing Using Arrays
  • File Input and Output with Arrays
  • Linear Algebra
  • Random Number Generation
  • Example: Random Walks

Getting Started with Pandas

  • Panda data structures
  • Essential Functionality
  • Summarizing and Computing Descriptive Statistics
  • Handling Missing Data
  • Hierarchical Indexing

Data Loading ,Storage, and File Formats

  • Reading and Writing data in Text Formats
  • Binary Data Formats
  • Interacting with HTML and Web APIS
  • Interacting with Databases

Data Wrangling: Clean, Transform, Merge, Reshape

  • Combining and Merging Data Sets
  • Reshaping and Pivoting
  • Data Transformation
  • String Manipulation

Plotting and Visualization

  • Matplotlib Primer
  • Plotting Functions in pandas
  • Plotting Maps

Plotting and Visualization

  • Matplotlib Primer
  • Plotting Functions in pandas
  • Plotting Maps

Data Aggregation and Group Operations

  • Group By Mechanics
  • Data Aggregation
  • Group-Wise Operations and Transformations
  • Pivot Tables and Cross-Tabulation

Time series

  • Date and Time Data Types and Tools
  • Time Series Basics
  • Date Ranges, Frequencies, and Shifting
  • Time Zone Handling
  • Periods and Period Arithmetic
  • Resampling and Frequency Conversion
  • Time Series Plotting
  • Moving Window Functions
  • Performance and Memory Usage Notes

Financial and Economic Data Applications

  • Data Munging Topics
  • Group Transforms and Analysis
  • More Example Applications

Advanced Numpy

  • ndarray Object Internals
  • Advanced Array Manipulation
  • Broadcasting
  • Advanced ufunc Usage
  • Structured and Record Arrays
  • More About Sorting
  • NumPy Matrix Class
  • Advanced Array Input and Output,Performance Tips
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