CO2412: Computational Thinking
Lecture 16
Introduction to Numeric Data Analysis
1. What is Numeric Data Analysis?
o Numeric data analysis involves summarizing and interpreting data
through various statistical measures to understand the distribution
and key characteristics of a data set.
2. Importance of Statistical Measures
o Statistical measures like mean, median, mode, variance, and
standard deviation provide insights into the distribution, variability,
and central values of data, which are crucial for making informed
decisions.
Measures of Central Tendency
1. Central Tendency Overview
o Central tendency refers to the central or typical value for a data set.
The key measures of central tendency are:
Arithmetic Mean
Median
Mode
Geometric Mean
2. Arithmetic Mean
o The arithmetic mean (often called the average) is the most common
measure of central tendency. It is calculated by summing all values
and dividing by the number of values.
o Formula: Mean=∑Xi/n
o The mean is sensitive to extreme values (outliers).
Lecture 16
Introduction to Numeric Data Analysis
1. What is Numeric Data Analysis?
o Numeric data analysis involves summarizing and interpreting data
through various statistical measures to understand the distribution
and key characteristics of a data set.
2. Importance of Statistical Measures
o Statistical measures like mean, median, mode, variance, and
standard deviation provide insights into the distribution, variability,
and central values of data, which are crucial for making informed
decisions.
Measures of Central Tendency
1. Central Tendency Overview
o Central tendency refers to the central or typical value for a data set.
The key measures of central tendency are:
Arithmetic Mean
Median
Mode
Geometric Mean
2. Arithmetic Mean
o The arithmetic mean (often called the average) is the most common
measure of central tendency. It is calculated by summing all values
and dividing by the number of values.
o Formula: Mean=∑Xi/n
o The mean is sensitive to extreme values (outliers).
