Introduction to Probability Distributions, Discrete Probability, Continuous Probability, Distribution Functions, Density Functions, Real life Examples of Probability Distributions
The post is about MCQs Discrete Probability Distribution. There are 20 multiple-choice questions. The quiz covers topics related to the basics of probability distribution, binomial probability distribution, hypergeometric probability distribution, and properties of probability distribution. Let us start with the MCQs Discrete Probability Distribution Quiz.
Online MCQs about Probability and Probability Distributions with Answers
MCQs Discrete Probability Distribution with Answers
Binomial distribution has parameters
In a binomial probability distribution, it is impossible to find
A fair coin is tossed four times, the probability of getting four heads is
Each trial in Binomial distribution has
The binomial distribution is negatively skewed when
In binomial distribution $n=6$ and $p=0.9$, then the value of $P(X=7)$ is
The binomial distribution is symmetrical when
In which distribution successive trials are without replacement
In hypergeometric distribution, the trials are
The probability of success changes from trial to trial in
The mean of the hypergeometric distribution is
Which of the following is not the property of binomial distribution
Successive trials in binomial distribution are
The mean, median, and mode for binomial distribution will be equal when
A random variable $X$ has binomial distribution with $n = 10$ and $p = 0.3$ then variance of $X$ is
If in a binomial distribution $n = 1$ then $E(X)$ is
The variance of the binomial distribution is always
This Quiz contains the MCQs Probability Distributions Quiz. It covers events, experiments, mutually exclusive events, collectively exhaustive events, sure events, impossible events, addition and multiplication laws of probability, concepts related to discrete and continuous random variables, probability distribution and probability density functions, characteristics and properties of probability distributions, discrete probability distribution, and continuous probability distributions, etc.
Probability distributions are the foundation for various statistical tests like hypothesis testing. By comparing observed data to a theoretical distribution (the null hypothesis), we can assess the likelihood that the data arose by chance.
Probability distributions are crucial tools in data analysis. They help identify patterns, outliers, and relationships between variables. Furthermore, many statistical models depend on specific probability distributions to function accurately.
Online MCQs Probability Distributions Quiz
In binomial probability distributions, the dependents of standard deviations must include
In binomial probability distribution, the formula for calculating standard deviation is
The formula of the mean of uniform or rectangular distribution is as
The normal distribution is also classified as
The mean deviation of a normal distribution is
The Chi-Square distribution is a special case of
Which of the distributions has a larger variance than its mean
For Beta distribution of 2nd kind, the range of $X$ is
The mean of the Poisson distribution is 9 then its standard deviation is
In normal distribution, the proportion of observations that lies between 1 standard deviation of the mean is closest to
For beta distribution of 1st kind, the range of $X$ is
The parameters of hypergeometric distributions are Note that $N$ is the population size, $n$ is the sample size, $p$ is the probability of successes, $K$ is a number of successes stated in the population, $k$ is the number of observed successes.
If $N$ is the population size, $n$ is the sample size, $p$ is the probability of success, $K$ is the number of successes stated in the population, and $k$ is the number of observed successes, then the parameters of the binomial distribution are
An oil company conducts a geological study that indicates that an exploratory oil well should have a 0.25 probability of striking oil. The company is interested in finding the probability that the 3rd strike comes on the 6th well drilled. Which distribution will be used?
If $X$ follows Geometric distribution with parameter $p$ (probability of success) then the Mean of $X$ is
The distribution of the square of the standard normal random variable will be
A random variable $X$ has a binomial distribution with $n=9$, the variance of $X$ is
In any normal distribution, the proportion of observations that are outside $\pm$ standard deviation of the mean is closest to
When can we use a normal distribution to approximate a binomial distribution?
An oil company conducts a geological study that indicates that an exploratory oil well should have a 20% chance of striking oil. The company is interested in finding the probability that the first strike comes on the third well drilled. Which distribution distribution will be used?
This Post is about the Online Probability Distributions Quiz and covers topics related to the Mean and Variance of random variables and the distribution of Random variables. MCQs Probability Random variable quiz requires knowledge of events, experiments, mutually exclusive events, collectively exhaustive events, sure events, impossible events, addition and multiplication laws of probability, concepts related to discrete and continuous random variables, probability distribution and probability density functions, characteristics and properties of probability distributions, discrete probability distribution, and continuous probability distributions, etc. To start with the Online Probability Distributions Quiz, click the links below.
Probability distributions are the foundation of understanding how likely different outcomes are in random events. Probability distributions describe the various possibilities (values) a random variable can take on and the associated probabilities of each possibility occurring.
There are two main categories of probability distributions:
Uses of Probability Distributions
Probability distributions are widely used in various fields, including:
Statistics: Form the foundation for statistical analysis and inference.
Finance: Used to model stock prices, investment returns, and risk analysis.
Machine Learning: Play a crucial role in algorithms for classification, prediction, and anomaly detection.
Engineering: Applied in reliability analysis, quality control, and signal processing.
Many other scientific disciplines: Used to model natural phenomena, analyze experimental data, and assess uncertainties.
Therefore, by understanding the concepts of probability distributions, we can
Calculate probabilities of specific events: Given a distribution (discrete or continuous), one can calculate the probability of a certain outcome or a range of outcomes occurring.
Make predictions about future events: By analyzing past data and fitting it to a probability distribution, one can make predictions about the likelihood of similar events happening in the future.
Compare outcomes from different scenarios: One can compare the probabilities of events associated with different choices or conditions.
By understanding probability distributions, you gain a powerful tool to analyze randomness, quantify uncertainty, and make informed decisions under uncertainty.
