stats-1__basic-stats.md

Index/ Python Data Analysis

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STATS-1: Basic Statistics

Generic

• Really good collection of video lecture series by Brandon Foltz
• Statistics and probability course from Khan Academy
• Highly recommend Practical Statistics for Data Scientists, 2nd Edition (Oreilly link, Amazon)

Population vs. Sample

• Population vs. Sample
• Population vs. Sample video from Khan academy
• Population vs. Sample video by Brandon Foltz
• Ch 2 : Data and Sampling Distributions of the book : 'Practical Statistics for Data Scientists' (Safari link, Amazon Link)

Variable Types

• Variable types
• Data types - video

Numerical Data Analysis

• Mean/Median/Mode - video by Brandon Foltz
• Standard deviation - video by Brandon Foltz
• Trimmed Mean
• Trimmed Mean - video

Summarizing/Describing Data

• Graphing categorical variables - video by Brandon Foltz
• Understanding histograms - video by Brandon Foltz

Covariance / Correlation

• Covariance - video by Brandon Foltz
• Correlation - video by Brandon Foltz
• Covariance Matrix - video by Brandon Foltz

Exploratory Data Analytics

• Ch 1 : Exploratory Data Analysis of the book : 'Practical Statistics for Data Scientists' (Safari link, Amazon Link)

Check List

You should be familiar with the following

• Population vs. sample
• Variable types (quantitative, discrete, continuous)
• Plot basic graphs
• Do numerical analysis such as mean, median, variance, standard deviation
• Correlation

Exercises

These are simple exercises designed to reinforce your learning so far.

Difficulty Level

★☆☆ - Easy
★★☆ - Medium
★★★ - Challenging
★★★★ - Bonus

EX-1 - Mean / Median / STD (★☆☆)

We have some sample salary data (in thousands) from two cities.

city1 = [15,12, 20, 25, 50, 35, 75, 80, 60, 45, 36]
city2 = [40,42, 45, 60, 55, 52, 56, 52, 62, 57, 48]

Calculate mean, median, variation, standard deviation for both city data.

EX-2 - NBA Player Stats (★★☆)

• Read nba player stats data
• Extract Salary column
• Find min/max/mean/median of salary
• Is there a large variance in salary? How will you find out?
• Find the 10% trimmed mean of salary
• Do some plots for salary
  Hint: boxplot and histograms

EX-3 - Correlation of NBA Player Stats (★★☆)

• Read nba player stats data
• Extract Height and Weight columns
• You will notice the height is in feet-inches format. For example 6-4. You will need to convert this to single numeric format.
  • Create a new column called height_cm
  • Conversion formula is:
    cm = feet * 30.48 + inches * 2.54
• Is there a correlation between height and weight ?
• Create a plot to illustrate the relationship

EX-4 - Correlation Matrix for House Sales Data (★★☆)

• Read house-sales.csv
• Create a correlation matrix for this data
• Analyze which attributes affect Saleprice

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