In this chapter, we will be learning about probability distributions.
We will start by understanding the concept of a random variable, which is a variable that takes on different values based on the outcome of a random event.
We will then explore the binomial distribution, which is used to calculate the probability of a specific number of successes in a fixed number of independent trials.
Next, we will delve into the normal distribution, which is a continuous probability distribution that is often used to model real-world phenomena.
Throughout this chapter, we will also compare and differentiate between discrete random variables, which can only take on certain values, and continuous random variables, which can take on any value within a range.
• Explain the meaning of random variable
• Compare and differentiate discrete random variable and continuous random variable
• Explain the meaning of probability distributions of discrete random variable
• Build the table and draw the graph of probability distributions of discrete random variable
• Explain the meaning of binomial distribution
• Determine the probability of an event for binomial distribution
• Interpret information, build table and draw the graph of binomial distribution
• Determine and explain the minimum value, variant, and standard deviation of binomial distribution
• Solving problems involving binomial distribution
• Investigate and explain the properties of the normal distribution graph
• Explain the meaning of standard normal distribution
• Determine and interpret the standard score, Z
• Determine the probability of an event for normal distribution
• Solving problems involving normal distributions
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