Lesson Notes By Weeks and Term v4 - SHS 1
STATISTICAL REASONING AND ITS APPLICATION IN REAL LIFE
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STATISTICAL REASONING AND ITS APPLICATION IN REAL LIFE
Download the Lessonotes Mobile Ghana app for faster lesson access on Android and iPhone.
Subject: Mathematics
Class: SHS 1
Term: 2nd Term
Week: 10
Grade code: 1.4.1.LI.2
Strand code: 4
Sub-strand code: 1
Content standard code: 1.4.1.CS.1
Indicator code: 1.4.1.LI.2
Theme: MAKING SENSE OF AND USING DATA
Subtheme: STATISTICAL REASONING AND ITS APPLICATION IN REAL LIFE
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In our daily lives, from the government planning for new schools to a waakye seller deciding how much food to cook, decisions are often based on information, or data. This lesson introduces us to the formal methods we can use to collect reliable numerical information (quantitative data). Understanding these methods is the first step in using statistics to make sense of the world around us, solve problems in our communities, and make informed decisions. We will explore five key methods for gathering data and learn how to choose the best one for a particular situation right here in our school or community.
A. What is Quantitative Data?
Before we collect data, we must know what type we are looking for. Quantitative Data: This is numerical data. It represents information that can be counted or measured. It answers questions like "How many?", "How much?", or "How often?". Examples in a Ghanaian context: The number of students in SHS 1 (e.g., 450 students) The height of a student in centimetres (e.g., 165 cm) The cost of a tro-tro ride from Madina to Circle (e.g., 7 GHS) The time it takes to walk from the dormitory to the classroom in minutes (e.g., 5 minutes) The score a student gets in a Mathematics test (e.g., 85 out of 100) Qualitative Data: This is non-numerical, descriptive data. It deals with qualities and characteristics. Examples: A student's favourite subject (e.g., "Mathematics"), the colour of a car (e.g., "Blue"), or feedback on the school's food ("The rice was tasty").
Our focus today is on collecting QUANTITATIVE data.
B. Quantitative Data Collection Methods