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Lecture notes

CO2412 Computational Thinking Lecture 16 Notes

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This document contains comprehensive notes from Lecture 16 of the CO2412 course on Computational Thinking, focusing on numeric data analysis. The lecture provides an in-depth overview of statistical measures used to summarize and interpret data, helping to understand the distribution and key characteristics of a data set.

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Uploaded on
August 20, 2024
Number of pages
3
Written in
2023/2024
Type
Lecture notes
Professor(s)
Amin amini
Contains
All classes

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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).

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