Lesson Notes By Weeks and Term v4 - SHS 3
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 3
Term: 2nd Term
Week: 13
Grade code: 3.4.1.LI.2
Strand code: 4
Sub-strand code: 1
Content standard code: 3.4.1.CS.1
Indicator code: 3.4.1.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 in Ghana, we often want to know if a new idea or action actually works. Does a new fertilizer improve crop yield? Does an extra class help students pass their WASSCE? Does a health campaign reduce malaria cases? Statistics provides us with tools to answer these questions. Today, we will learn how to use a powerful visual tool called a scatter graph to analyse data from simple experiments, helping us see relationships and make informed decisions. This skill is crucial not just for mathematics, but for science, business, and understanding the world around us.
Concept 1: Experimental Studies (Pre-test/Post-test Design)
An experimental study is a method where we investigate the effect of an intervention (a treatment or action) on a group. The NaCCA exemplars focus on a simple but common type: the pre-test/post-test design. Pre-test: A measurement taken *before* the intervention or treatment is applied. (e.g., a student's test score before attending extra classes). Intervention/Treatment: The action or programme being studied. (e.g., the extra classes). Post-test: A measurement taken *after* the intervention. (e.g., the student's test score after attending the extra classes).
By comparing the pre-test and post-test results for the same group of individuals, we can see if the intervention had an effect. Concept 2: Bivariate Data and Variables Bivariate Data: This simply means data that has two variables for each observation. In our pre-test/post-test studies, the two variables for each person are their 'before' score and their 'after' score. Independent Variable (X-axis): This is the variable that we think might cause a change. In our context, it is the pre-test score. We plot this on the horizontal axis (x-axis). Dependent Variable (Y-axis): This is the variable that we measure to see if it has been affected by the intervention. It is the post-test score. We plot this on the vertical axis (y-axis). We are checking if the 'after' score *depends* on the 'before' score and the intervention. Concept 3: Scatter Graphs (Scatterplots)
A scatter graph is a graph that uses dots to show the relationship between two numerical variables. Each dot on the graph represents one subject's pair of scores (e.g., one student's pre-test and post-test scores).