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    STAT2115

    Introduction to Statistics

    Progress0 / 24 done
    Topics24
    1Scope of Statistics
    2Descriptive and Inferential Statistics3Population, Sample, Parameter, and Statistic4Types of Data and Scales of Measurement5Frequency Distribution and Graphical Representation6Bar Chart, Pie Chart, and Histogram7Frequency Polygon, Frequency Curve, and Cumulative Frequency Polygon8Measures of Central Tendency9Quantiles10Absolute and Relative Measures of Dispersion11Moments, Skewness and Kurtosis12Basic Concepts of Probability
    13Multiplication Principle, Permutation and Combination14Probability Spaces and Laws of Probability15Conditional Probability and Bayes' Theorem16Discrete and Continuous Random Variables
    17Binomial, Poisson, and Hypergeometric18Uniform, Exponential, and Normal
    19Sample Design and Sampling Frame20Sampling and Non-Sampling Errors21Sampling Distributions for Mean and Proportion22Sampling Distributions for Difference of Means and Difference of Proportions23Overview of Hypothesis Testing24Overview of Regression Analysis
    5 min read
    Topic 13 of 24
    Topic Study Note Illustration
    13

    Counting Rules: Multiplication Principle, Permutation and Combination

    The Multiplication Principle is used to find the total number of outcomes of a sequence of events .

    1. Multiplication Principle (Fundamental Counting Principle)

    The Multiplication Principle is used to find the total number of outcomes of a sequence of events.

    • Rule: If an operation can be performed in mmm ways and a second operation in nnn ways, then the total number of ways both can occur is:

      Total ways=m×n\text{Total ways} = m \times nTotal ways=m×n
    • Example:

      • A shirt can be red or blue (2 options) and pants can be black or white (2 options).
      • Total outfits = 2×2=42 \times 2 = 42×2=4
    • Extension: For kkk operations with n1,n2,...,nkn_1, n_2, ..., n_kn1​,n2​,...,nk​ ways:

      Total ways=n1×n2×...×nk\text{Total ways} = n_1 \times n_2 \times ... \times n_kTotal ways=n1​×n2​×...×nk​

    2. Permutation

    Permutation refers to the arrangement of objects in a specific order. Order matters in permutation.

    Formulas

    1. Permutation of nnn distinct objects (all objects):

      Pn=n!=n⋅(n−1)⋅(n−2)⋯1P_n = n! = n \cdot (n-1) \cdot (n-2) \cdots 1Pn​=n!=n⋅(n−1)⋅(n−2)⋯1
    2. Permutation of rrr objects out of nnn (ordered selection):

      P(n,r)=n!(n−r)!P(n, r) = \frac{n!}{(n-r)!}P(n,r)=(n−r)!n!​
    • Example: How many ways can 3 students be seated in 5 chairs? P(5,3)=5!(5−3)!=1202=60P(5, 3) = \frac{5!}{(5-3)!} = \frac{120}{2} = 60P(5,3)=(5−3)!5!​=2120​=60
    1. Permutation with repetition (if some objects are identical): Total arrangements=n!p1!,p2!,...,pk!\text{Total arrangements} = \frac{n!}{p_1! , p_2! , ... , p_k!}Total arrangements=p1​!,p2​!,...,pk​!n!​
    • Where p1,p2,...,pkp_1, p_2, ..., p_kp1​,p2​,...,pk​ are counts of identical objects.
    • Example: ARRANGE letters in "LEVEL" → 5!/(2!2!)=305!/ (2!2!) = 305!/(2!2!)=30

    3. Combination

    Combination refers to selection of objects where order does not matter.

    Formula

    C(n,r)=(nr)=n!r!(n−r)!C(n, r) = \binom{n}{r} = \frac{n!}{r!(n-r)!}C(n,r)=(rn​)=r!(n−r)!n!​
    • Example: How many ways to choose 3 students from 5? C(5,3)=5!3!2!=1206⋅2=10C(5,3) = \frac{5!}{3!2!} = \frac{120}{6 \cdot 2} = 10C(5,3)=3!2!5!​=6⋅2120​=10

    Relationship Between Permutation and Combination

    P(n,r)=C(n,r)⋅r!P(n, r) = C(n, r) \cdot r!P(n,r)=C(n,r)⋅r!
    • Because each combination of rrr objects can be arranged in r!r!r! ways.

    Quick Tips to Remember

    Concept Order Important? Formula Example
    Multiplication Principle N/A Multiply options Shirt & pants
    Permutation Yes P(n,r)=n!/(n−r)!P(n,r) = n!/(n-r)!P(n,r)=n!/(n−r)! Seats, races
    Combination No C(n,r)=n!/(r!(n−r)!)C(n,r) = n!/(r!(n-r)!)C(n,r)=n!/(r!(n−r)!) Teams, committees

    Key Points

    1. Use Multiplication Principle when counting sequences of independent events.
    2. Use Permutations when arrangement matters.
    3. Use Combinations when only selection matters.
    4. Remember: P(n,r)=C(n,r)⋅r!P(n, r) = C(n, r) \cdot r!P(n,r)=C(n,r)⋅r!
    ← Previous topic 12
    Basic Concepts of Probability
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    Probability Spaces and Laws of Probability

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