Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
5. Binomial Distribution & Discrete Random Variables
Discrete Random Variables
Problem 4.1.6
Textbook Question
True or False? In Exercises 5–8, determine whether the statement is true or false. If it is false, rewrite it as a true statement.
For a random variable x, the word random indicates that the value of x is determined by chance.

1
Understand the definition of a random variable: A random variable is a numerical outcome of a random phenomenon, and its value is determined by chance.
Analyze the statement: 'For a random variable x, the word random indicates that the value of x is determined by chance.'
Compare the statement to the definition of a random variable. The key aspect is whether the value of x being determined by chance aligns with the definition.
Determine if the statement is true or false based on the comparison. If it matches the definition, the statement is true. If not, identify the discrepancy.
If the statement is false, rewrite it to align with the correct definition of a random variable, ensuring clarity and accuracy.

This video solution was recommended by our tutors as helpful for the problem above
Video duration:
1mPlay a video:
Was this helpful?
Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Random Variable
A random variable is a numerical outcome of a random phenomenon. It can take on different values, each associated with a probability, reflecting the uncertainty inherent in the process. Random variables are classified into discrete (specific values) and continuous (any value within a range) types, which are fundamental in probability and statistics.
Recommended video:
Guided course
Intro to Random Variables & Probability Distributions
Probability
Probability is a measure of the likelihood that a particular event will occur, expressed as a number between 0 and 1. In the context of random variables, it quantifies the chance of each possible outcome. Understanding probability is essential for interpreting random variables and making predictions based on statistical data.
Recommended video:
Introduction to Probability
Determinism vs. Randomness
Determinism refers to the idea that events are determined by preceding causes, while randomness implies that outcomes are influenced by chance. In statistics, recognizing the distinction between deterministic and random processes is crucial for accurately modeling and analyzing data, particularly when dealing with random variables.
Recommended video:
Guided course
Coefficient of Determination
Watch next
Master Intro to Random Variables & Probability Distributions with a bite sized video explanation from Patrick
Start learningRelated Videos
Related Practice