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<!DOCTYPE html>
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    <title>Statistics and Probability</title>
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    <header>
        <h1>Statistics and Probability</h1>
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    <div class="content">
        <h2>1. Statistics</h2>
        <p>Statistics is the study of data collection, organization, analysis, interpretation, and presentation.</p>

        <h3>1.1 Types of Statistics</h3>
        <ul>
            <li><strong>Descriptive Statistics</strong> – Summarizes data (e.g., mean, median, mode).</li>
            <li><strong>Inferential Statistics</strong> – Makes predictions using samples.</li>
        </ul>

        <h3>1.2 Measures of Central Tendency</h3>
        <ul>
            <li><strong>Mean:</strong> (Sum of all values) ÷ (Number of values)</li>
            <li><strong>Median:</strong> The middle value when data is arranged in order.</li>
            <li><strong>Mode:</strong> The most frequently occurring value.</li>
        </ul>

        <div class="note">
            <strong>Note:</strong> The mean is sensitive to outliers, while the median is more resistant to extreme values.
        </div>

        <h3>1.3 Measures of Dispersion</h3>
        <ul>
            <li><strong>Range:</strong> Maximum value - Minimum value</li>
            <li><strong>Variance:</strong> Average of squared differences from the mean.</li>
            <li><strong>Standard Deviation:</strong> Square root of variance.</li>
        </ul>

        <h2>2. Probability</h2>
        <p>Probability is the measure of how likely an event is to occur, expressed as a number between 0 and 1.</p>

        <h3>2.1 Probability Rules</h3>
        <ul>
            <li><strong>Addition Rule:</strong> P(A or B) = P(A) + P(B) - P(A and B)</li>
            <li><strong>Multiplication Rule:</strong> P(A and B) = P(A) × P(B), if A and B are independent</li>
            <li><strong>Conditional Probability:</strong> P(A given B) = P(A and B) ÷ P(B)</li>
        </ul>

        <div class="note">
            <strong>Example:</strong> If rolling a die, the probability of getting a 3 is 1/6.
        </div>

        <h3>2.2 Bayes' Theorem</h3>
        <p>P(A given B) = [P(B given A) × P(A)] ÷ P(B)</p>

        <h3>2.3 Probability Distributions</h3>
        <ul>
            <li><strong>Binomial Distribution:</strong> Probability of exactly k successes in n trials.</li>
            <li><strong>Poisson Distribution:</strong> Probability of a given number of events in a fixed interval.</li>
            <li><strong>Normal Distribution:</strong> Bell-shaped curve describing many natural events.</li>
        </ul>

        <div class="note">
            <strong>Tip:</strong> The normal distribution is used in standardized tests like IQ scores.
        </div>
    </div>

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        <p>&copy; 2025 Yoseph Feyisa Wegi | All Rights Reserved.</p>
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