Random Variables: Discrete vs Continuous, Distributions, and Examples
A lesson in discrete and continuous random variables that moves from intuition and definitions to worked reasoning, error correction, and independent practice.
Lesson Goals: Random Variable
A random variable maps outcomes to numbers; a discrete distribution assigns probabilities that sum to one, while a continuous density assigns probability through area over intervals.
Definition
Definition in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Definition in random variable, A constructed discrete random variable for a city bus arrival investigation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
When the idea is valid
For Definition in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Definition in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Discrete random variables
Discrete random variables in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Discrete random variables in random variable, A constructed discrete random variable for a water-filtration experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
When the idea is valid
For Discrete random variables in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Discrete random variables in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Continuous random variables
Continuous random variables in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Continuous random variables in random variable, A constructed discrete random variable for a quality-control inspection has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
When the idea is valid
For Continuous random variables in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Continuous random variables in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Probability distributions
Probability distributions in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Probability distributions in random variable, A constructed discrete random variable for a public-parks visitor survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
When the idea is valid
For Probability distributions in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Probability distributions in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Valid distribution conditions
Valid distribution conditions in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Valid distribution conditions in random variable, A constructed discrete random variable for a school library checkout study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
When the idea is valid
For Valid distribution conditions in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Valid distribution conditions in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Examples
Examples in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Examples in random variable, A constructed discrete random variable for a school library checkout study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
When the idea is valid
For Examples in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Examples in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Transformations
Transformations in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Transformations in random variable, A constructed discrete random variable for a commuter route study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
When the idea is valid
For Transformations in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Transformations in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Practice
Practice in random variable: The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value.
Worked reasoning
For Practice in random variable, A constructed discrete random variable for a quality-control inspection has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
When the idea is valid
For Practice in random variable, List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
Misconception to remove
For Practice in random variable, reject this error: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Formula and Notation Reference
Discrete probability total
Discrete probability total in Random Variable: This expression belongs specifically to discrete and continuous random variables; define every symbol and apply the scope rule for support, probability distributions, density, cumulative probability, and notation before calculation.
Continuous interval probability
Continuous interval probability in Random Variable: Define the event or random variable first; complements, conditioning, and trial assumptions determine which probability expression applies.
Guided, Independent and Challenge Practice
Every question in Random Variables: Discrete vs Continuous, Distributions, and Examples is newly written from the revised framework and the logic visible in public College Board materials. Constructed numerical settings are identified as instructional scenarios and are never represented as measurements from a real population. No released or secure question wording is reproduced.
Easy Practice
Easy 1: Definition
Question P43-Easy-1. A constructed discrete random variable for a seedling-growth comparison has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Easy-1. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 2: Discrete random variables
Question P43-Easy-2. A constructed discrete random variable for a website response-time study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
Worked solution and validity check
Worked solution P43-Easy-2. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 3: Continuous random variables
Question P43-Easy-3. A constructed discrete random variable for a classroom memory study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
Worked solution and validity check
Worked solution P43-Easy-3. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 4: Probability distributions
Question P43-Easy-4. A constructed discrete random variable for a recycling-behavior survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
Worked solution and validity check
Worked solution P43-Easy-4. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 5: Valid distribution conditions
Question P43-Easy-5. A constructed discrete random variable for a battery-life laboratory trial has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
Worked solution and validity check
Worked solution P43-Easy-5. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 6: Examples
Question P43-Easy-6. A constructed discrete random variable for a recycling-behavior survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Easy-6. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 7: Transformations
Question P43-Easy-7. A constructed discrete random variable for a public-parks visitor survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
Worked solution and validity check
Worked solution P43-Easy-7. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 8: Practice
Question P43-Easy-8. A constructed discrete random variable for a commuter route study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
Worked solution and validity check
Worked solution P43-Easy-8. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 9: Definition
Question P43-Easy-9. A constructed discrete random variable for a reading-speed investigation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Easy-9. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 10: Discrete random variables
Question P43-Easy-10. A constructed discrete random variable for a campus dining survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
Worked solution and validity check
Worked solution P43-Easy-10. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 11: Continuous random variables
Question P43-Easy-11. A constructed discrete random variable for a package-delivery sample has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
Worked solution and validity check
Worked solution P43-Easy-11. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 12: Probability distributions
Question P43-Easy-12. A constructed discrete random variable for a public-parks visitor survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
Worked solution and validity check
Worked solution P43-Easy-12. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 13: Valid distribution conditions
Question P43-Easy-13. A constructed discrete random variable for a package-delivery sample has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
Worked solution and validity check
Worked solution P43-Easy-13. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Easy 14: Examples
Question P43-Easy-14. A constructed discrete random variable for a water-filtration experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Easy-14. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough Practice
Tough 1: Probability distributions
Question P43-Tough-1. A constructed discrete random variable for a seedling-growth comparison has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
Worked solution and validity check
Worked solution P43-Tough-1. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 2: Valid distribution conditions
Question P43-Tough-2. A constructed discrete random variable for a greenhouse germination experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
Worked solution and validity check
Worked solution P43-Tough-2. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 3: Examples
Question P43-Tough-3. A constructed discrete random variable for a tutoring-program evaluation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Tough-3. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 4: Transformations
Question P43-Tough-4. A constructed discrete random variable for a battery-life laboratory trial has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
Worked solution and validity check
Worked solution P43-Tough-4. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 5: Practice
Question P43-Tough-5. A constructed discrete random variable for a seedling-growth comparison has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
Worked solution and validity check
Worked solution P43-Tough-5. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 6: Definition
Question P43-Tough-6. A constructed discrete random variable for a city bus arrival investigation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Tough-6. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 7: Discrete random variables
Question P43-Tough-7. A constructed discrete random variable for a commuter route study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
Worked solution and validity check
Worked solution P43-Tough-7. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 8: Continuous random variables
Question P43-Tough-8. A constructed discrete random variable for a public-parks visitor survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
Worked solution and validity check
Worked solution P43-Tough-8. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 9: Probability distributions
Question P43-Tough-9. A constructed discrete random variable for a tutoring-program evaluation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
Worked solution and validity check
Worked solution P43-Tough-9. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 10: Valid distribution conditions
Question P43-Tough-10. A constructed discrete random variable for a classroom memory study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
Worked solution and validity check
Worked solution P43-Tough-10. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 11: Examples
Question P43-Tough-11. A constructed discrete random variable for a water-filtration experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Tough-11. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 12: Transformations
Question P43-Tough-12. A constructed discrete random variable for a commuter route study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
Worked solution and validity check
Worked solution P43-Tough-12. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 13: Practice
Question P43-Tough-13. A constructed discrete random variable for a website response-time study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
Worked solution and validity check
Worked solution P43-Tough-13. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Tough 14: Definition
Question P43-Tough-14. A constructed discrete random variable for a website response-time study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Tough-14. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest Practice
Toughest 1: Examples
Question P43-Toughest-1. A constructed discrete random variable for a campus dining survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Toughest-1. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 2: Transformations
Question P43-Toughest-2. A constructed discrete random variable for a school library checkout study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
Worked solution and validity check
Worked solution P43-Toughest-2. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 3: Practice
Question P43-Toughest-3. A constructed discrete random variable for a seedling-growth comparison has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
Worked solution and validity check
Worked solution P43-Toughest-3. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 4: Definition
Question P43-Toughest-4. A constructed discrete random variable for a battery-life laboratory trial has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Toughest-4. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 5: Discrete random variables
Question P43-Toughest-5. A constructed discrete random variable for a package-delivery sample has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
Worked solution and validity check
Worked solution P43-Toughest-5. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 6: Continuous random variables
Question P43-Toughest-6. A constructed discrete random variable for a city bus arrival investigation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
Worked solution and validity check
Worked solution P43-Toughest-6. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 7: Probability distributions
Question P43-Toughest-7. A constructed discrete random variable for a commuter route study has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for probability distributions.
Worked solution and validity check
Worked solution P43-Toughest-7. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 8: Valid distribution conditions
Question P43-Toughest-8. A constructed discrete random variable for a greenhouse germination experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for valid distribution conditions.
Worked solution and validity check
Worked solution P43-Toughest-8. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 9: Examples
Question P43-Toughest-9. A constructed discrete random variable for a greenhouse germination experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for examples.
Worked solution and validity check
Worked solution P43-Toughest-9. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 10: Transformations
Question P43-Toughest-10. A constructed discrete random variable for a water-filtration experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for transformations.
Worked solution and validity check
Worked solution P43-Toughest-10. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 11: Practice
Question P43-Toughest-11. A constructed discrete random variable for a seedling-growth comparison has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for practice.
Worked solution and validity check
Worked solution P43-Toughest-11. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 12: Definition
Question P43-Toughest-12. A constructed discrete random variable for a tutoring-program evaluation has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for definition.
Worked solution and validity check
Worked solution P43-Toughest-12. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 13: Discrete random variables
Question P43-Toughest-13. A constructed discrete random variable for a public-parks visitor survey has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for discrete random variables.
Worked solution and validity check
Worked solution P43-Toughest-13. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
Toughest 14: Continuous random variables
Question P43-Toughest-14. A constructed discrete random variable for a greenhouse germination experiment has values [0, 1, 2, 4] with probabilities [0.2, 0.35, 0.3, 0.15]. Verify the distribution and find for continuous random variables.
Worked solution and validity check
Worked solution P43-Toughest-14. The distribution is valid because all probabilities are nonnegative and sum to 1; . Interpretation: The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. Validity: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. Error to reject: A continuous random variable has probability zero at any single exact value even though intervals can have positive probability.
AP Response and Publication Checklist
| Audit point | Required evidence for random variable |
|---|---|
| Scope | P44 owns mean and standard deviation calculations; P45 owns binomial structure. |
| Method or source | A random variable maps outcomes to numbers; a discrete distribution assigns probabilities that sum to one, while a continuous density assigns probability through area over intervals. |
| Calculation | |
| Interpretation | The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. |
| Validity | List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X. |
| Correction | A continuous random variable has probability zero at any single exact value even though intervals can have positive probability. |
Frequently Asked Questions
How does definition work in random variable?
Answer for random variable and Definition. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does discrete random variables work in random variable?
Answer for random variable and Discrete random variables. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does continuous random variables work in random variable?
Answer for random variable and Continuous random variables. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does probability distributions work in random variable?
Answer for random variable and Probability distributions. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does valid distribution conditions work in random variable?
Answer for random variable and Valid distribution conditions. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does examples work in random variable?
Answer for random variable and Examples. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. The required validity evidence is: List the support completely and distinguish a probability mass function for discrete X from area under a density for continuous X.
How does discrete random variable connect to Random Variable?
discrete random variable within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Definition, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does variable and random variable connect to Random Variable?
variable and random variable within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Discrete random variables, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does continuous random variable connect to Random Variable?
continuous random variable within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Continuous random variables, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does what is a random variable connect to Random Variable?
what is a random variable within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Probability distributions, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does discrete random variables connect to Random Variable?
discrete random variables within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Valid distribution conditions, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does what random variable connect to Random Variable?
what random variable within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Examples, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
How does random variables connect to Random Variable?
random variables within random variable. The distribution is valid because all probabilities are nonnegative and sum to 1; . The random variable maps each outcome of the process to a numerical value; its distribution assigns long-run probability to each possible value. For Transformations, the controlling scope is: P44 owns mean and standard deviation calculations; P45 owns binomial structure.
Sources
Administrative and curricular statements in Random Variables: Discrete vs Continuous, Distributions, and Examples were checked on July 18, 2026. The linked College Board pages control any later policy change; all instructional datasets in original questions are explicitly constructed rather than attributed to a real study.
Random Variable Conclusion
A random variable maps outcomes to numbers; a discrete distribution assigns probabilities that sum to one, while a continuous density assigns probability through area over intervals. Mastery of random variable therefore requires the exact evidence, mathematics, interpretation, and scope developed in this guide, while preserving this boundary: P44 owns mean and standard deviation calculations; P45 owns binomial structure.