Lesson Notes By Weeks and Term v4 - SHS 1
MAKING PREDICTIONS WITH DATA
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MAKING PREDICTIONS WITH DATA
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Subject: Additional Mathematics
Class: SHS 1
Term: 2nd Term
Week: 20
Grade code: 1.4.2.LI.6
Strand code: 4
Sub-strand code: 2
Content standard code: 1.4.2.CS.1
Indicator code: 1.4.2.LI.6
Theme: HANDLING DATA
Subtheme: MAKING PREDICTIONS WITH DATA
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This lesson introduces the foundational concepts of probability by exploring the difference between what *should* happen in theory and what *actually* happens in a real experiment. We often make predictions in our daily lives in Ghana – from a farmer predicting the rainy season to a trotro driver estimating traffic time, or even deciding if you should carry an umbrella. This lesson will give you the mathematical tools to understand and test these kinds of predictions using data.
This section breaks down the core ideas you need to master. We will use simple, local examples to make it clear. A. Basic Probability Terms Experiment: An action or process with an uncertain result. *Example:* Tossing a 1 Ghana Cedi coin. Outcome: A single possible result of an experiment. *Example:* When tossing a coin, the possible outcomes are *Head* or *Tail*. Sample Space (S): The set of ALL possible outcomes of an experiment. *Example:* For tossing a coin, S = {Head, Tail}. For rolling a Ludo die, S = {1, 2, 3, 4, 5, 6}. Event (E): A specific outcome or a set of outcomes you are interested in. *Example:* The event of getting a *Head* when tossing a coin. The event of rolling an *even number* on a die (which includes outcomes {2, 4, 6}). B. Relative Frequency (Experimental Probability)
This is the probability of an event happening based on the results of an actual experiment. It is what you *observe* happening.
The formula is: Relative Frequency = (Number of times the event occurred) / (Total number of trials)
Let's see this in action.