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Summary STK 210 Statistics – Discrete Probability Distributions Explained | PMF, CDF, Binomial & Hypergeometric (Study Guide)

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These study notes explain discrete probability distributions used in statistics for STK 210. The document provides clear explanations and worked examples to help students understand how probability distributions are constructed and interpreted. Topics covered include: • Sample spaces and random variables • Discrete random variables and their ranges • Probability mass functions (PMF) • Cumulative distribution functions (CDF) • Calculating probabilities using PMF and CDF • Median, quartiles and interquartile range from CDF • Binomial distribution with examples (coin tosses) • Hypergeometric distribution (sampling without replacement) • Converting CDF to PMF These notes are useful for: • Exam preparation • Understanding probability distributions • Solving discrete probability problems in statistics courses.

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CHAPTER 3A — DISCRETE PROBABILITY
DISTRIBUTIONS (UNIVARIATE)
This chapter has 4 big parts:
1. Discrete Random Variables
2. Probability Distributions (PMF / PDF for discrete)
3. Distribution Functions (CDF)
4. Examples:
o Dice
o Coin (Binomial)
o Socks (Hypergeometric)
o Accidents (Given CDF → find pdf)
We will go step by step.


PART 1: DISCRETE RANDOM VARIABLES
What is a Sample Space?
The sample space (S) is:
The set of all possible outcomes of an experiment.
Example: Roll two dice
Each die has numbers 1 to 6.
If you roll two dice:
Possible outcomes are ordered pairs:
(1,1), (1,2), …, (6,6)
Total outcomes:
6 × 6 = 36
So:
S = { (1,1), (1,2), … , (6,6) }
There are 36 sample points.


What is a Random Variable?
A random variable:
A function that assigns a number to each outcome in the sample space.
Very important:
• Random variables are written in CAPITAL letters (X)
• Values are written in lowercase (x)

, Dice Example
Define:
X = total number of points when rolling 2 dice
So:
If outcome is (3,5), then:
X=3+5=8
If outcome is (6,6), then:
X = 12


What is the Range of X?
Minimum total:
1+1=2
Maximum total:
6 + 6 = 12
So:
Range of X = {2, 3, 4, … , 12}
This is a finite set, so X is a discrete random variable.


What is a Discrete Random Variable?
A random variable is discrete if:
• Its values are finite
OR
• Countably infinite (like 1,2,3,4,...)
Examples:
• Number of bedrooms (finite)
• Number of coin tosses until heads (countable infinite)

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