The sum of probabilities in a probability distribution must equal 1
Match the type of probability distribution with its description:
Discrete ↔️ Finite set of distinct values
Continuous ↔️ Any value within a range
The probabilities in a discrete probability distribution must add up to 1.
True
What does the Binomial distribution describe?
Number of successes in trials
What are the key components of a probability distribution?
Possible outcomes, probabilities
What is a probability distribution?
A mathematical function
A probability distribution for tossing a fair coin shows that heads and tails each have a probability of 0.5.
True
The key characteristic of a discrete probability distribution is that its probabilities must add up to 1
The Poisson distribution assumes a fixed number of trials and a constant probability of success per trial.
False
The Normal distribution is also known as the Gaussian distribution.
The Exponential distribution is right-skewed.
True
Match the continuous probability distribution with its property:
Normal ↔️ Bell-shaped, symmetrical
Exponential ↔️ Right-skewed, no memory
The Binomial distribution assumes a fixed number of trials and a constant probability of success per trial.
The sum of all probabilities in a probability distribution must equal 1.
True
A probability distribution is a mathematical function that describes the possible values a random variable can take and their associated probabilities.
What are the three key components of a probability distribution?
Possible outcomes, probabilities, sum
Discrete probability distributions describe the probability of a random variable taking on a finite set of distinct values.
Match the distribution with its definition:
Binomial ↔️ Successes in fixed trials
Poisson ↔️ Events in a fixed interval
The Normal distribution is characterized by its mean and standard deviation.
The Exponential distribution is characterized by its rate parameter.
Match the distribution with its key property:
Normal ↔️ Bell-shaped, symmetrical
Exponential ↔️ Right-skewed
All outcomes in a Uniform distribution are equally likely.
True
Match the scenario with the appropriate probability distribution:
Waiting times ↔️ Exponential
Heights and weights ↔️ Normal
What is a probability distribution?
Table or graph showing probabilities
A probability distribution shows what outcomes are possible and how likely they are to occur.
True
The Binomial and Poisson distributions are examples of discrete probability distributions.
Compare the Binomial and Poisson distributions based on their assumptions:
1️⃣ Binomial: Fixed number of trials, constant probability of success per trial
2️⃣ Poisson: Events occur independently at a constant average rate
Continuous probability distributions describe random variables taking on any value within a range
The sum of probabilities in a probability distribution must equal 1.
True
The sum of all probabilities in a probability distribution must equal 1
What does a discrete probability distribution describe?
Finite set of values
Match the discrete probability distribution with its description:
Binomial ↔️ Successes in fixed trials
Poisson ↔️ Events in fixed interval
What is a continuous probability distribution?
Values within a range
What is a key property of the Normal distribution?
Symmetry around the mean
What is a key difference between the Uniform and Binomial distributions?
Equally likely outcomes vs. successes in fixed trials
What is the purpose of a probability distribution?
Describe possible outcomes and probabilities
Order the following steps to create a probability distribution:
1️⃣ Identify possible outcomes
2️⃣ Determine the probability of each outcome
3️⃣ Ensure the probabilities sum to 1
The sum of probabilities in a probability distribution must equal 1.
True
The probabilities in a discrete probability distribution must add up to 1.
True
What are two common examples of continuous probability distributions?