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Module 3 - Exploratory Data Analysis.md

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Module 3 - Exploratory Data Analysis.md

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Learning Objective

  • Descriptive Statistics
  • Basic of Grouping
  • ANOVA
  • Correlation

Practice Quiz: Descriptive Statistics

Question 1: Consider the following scatter plot; what kind of relationship do the two variables have?

2-5

  • A. [X] positive linear relationship
  • B. [ ] negative linear relationship

Practice Quiz: GroupBy in Python

Question 1: Select the appropriate description of a pivot table:

  • A. [ ] A pivot table contains statistical information for each column.
  • B. [X] A pivot table has one variable displayed along the columns and the other variable displayed along the rows.

Practice Quiz: Correlation

Question 1: Select the scatter plot with weak correlation:

  • A. [ ]

2-7

  • B. [X]

2-8

Practice Quiz: Correlation - Statistics

Question 1: Consider the following scatter plots a,b and c. What plot would have the highest correlation coefficient? (Note: this one is harder than it seems)

2-12

  • A. [ ] a
  • B. [ ] b
  • C. [ ] c
  • D. [X] They all have the same value

Lesson Summary

In this lesson, you have learned how to:

  • Describe Exploratory Data Analysis: By summarizing the main characteristics of the data and extracting valuable insights.
  • Compute basic descriptive statistics: Calculate the mean, median, and mode using python and use it as a basis in understanding the distribution of the data.
  • Create data groups: How and why you put continuous data in groups and how to visualize them.
  • Define correlation as the linear association between two numerical variables: Use Pearson correlation as a measure of the correlation between two continuous variables
  • Define the association between two categorical variables: Understand how to find the association of two variables using the Chi-square test for association and how to interpret them.

Exploratory Data Analysis

Exploratory Data Analysis

Graded Quiz: Exploratory Data Analysis

Question 1: What task does the method value_counts perform?

  • A. [ ] Returns summary statistics
  • B. [ ] Returns the first five columns of a dataframe
  • C. [X] Returns counts of unique values

Question 2: What is the largest possible element resulting in the operation df.corr()?

  • A. [X] 1
  • B. [ ] 100
  • C. [ ] 1000

Question 3: If the Pearson Correlation between two variables is zero, then ...

  • A. [ ] The two variables have zero mean
  • B. [X] The two variables are not correlated

Question 4: Consider the dataframe df;what method displays the first five rows of a dataframe?

  • A. [X] df.head()
  • B. [ ] df.describe()
  • C. [ ] df.tail()

Question 5: What is the Pearson Correlation between variables X and Y, if X=-Y?

  • A. [X] -1
  • B. [ ] 1
  • C. [ ] 0