If you're seeing this message, it means we're having trouble loading external resources on our website. Show If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked. A type of variable in statistics whose possible values depend on the outcomes of a certain random phenomenon A random variable (stochastic variable) is a type of variable in statistics whose possible values depend on the outcomes of a certain random phenomenon. Since a random variable can take on different values, it is commonly labeled with a letter (e.g., variable “X”). Each variable possesses a specific probability distribution function (a mathematical function that represents the probabilities of occurrence of all possible outcomes). Types of Random VariablesRandom variables are classified into discrete and continuous variables. The main difference between the two categories is the type of possible values that each variable can take. In addition, the type of (random) variable implies the particular method of finding a probability distribution function. 1. DiscreteA discrete random variable is a (random) variable whose values take only a finite number of values. The best example of a discrete variable is a dice. Throwing a dice is a purely random event. At the same time, the dice can take only a finite number of outcomes {1, 2, 3, 4, 5, and 6}. Each outcome of a discrete random variable contains a certain probability. For example, the probability of each dice outcome is 1/6 because the outcomes are of equal probabilities. Note that the total probability outcome of a discrete variable is equal to 1. 2. ContinuousUnlike discrete variables, continuous random variables can take on an infinite number of possible values. One of the examples of a continuous variable is the returns of stocks. The returns can take an infinite number of possible values (as percentages). Due to the above reason, the probability of a certain outcome for the continuous random variable is zero. However, there is always a non-negative probability that a certain outcome will lie within the interval between two values. Random Variables in FinanceIn finance, random variables are widely used in financial modeling, scenario analysis, and risk management. In financial models and simulations, the probabilities of the variables represent the probabilities of random phenomena that affect the price of a security or determine the risk level of an investment. For instance, a variable may be applied to indicate the price of an asset at some point in the future or signal the occurrence of an adverse event. More ResourcesCFI is the official provider of the global Financial Modeling & Valuation Analyst (FMVA)™ certification program, designed to help anyone become a world-class financial analyst. To keep learning and advancing your career, the additional CFI resources below will be useful: Variable refers to the quantity that changes its value, which can be measured. It is of two types, i.e. discrete or continuous variable. The former refers to the one that has a certain number of values, while the latter implies the one that can take any value between a given range. Data can be understood as the quantitative information about a specific characteristic. The characteristic can be qualitative or quantitative, but for the purpose of statistical analysis, the qualitative characteristic is transformed into quantitative one, by providing numerical data of that characteristic. So, the quantitative characteristic is known as a variable. Here in this article, we are going to talk about the discrete and continuous variable. Content: Discrete Variable Vs Continuous Variable
Comparison Chart
Definition of Discrete VariableA discrete variable is a type of statistical variable that can assume only fixed number of distinct values and lacks an inherent order. Also known as a categorical variable, because it has separate, invisible categories. However no values can exist in-between two categories, i.e. it does not attain all the values within the limits of the variable. So, the number of permitted values that it can suppose is either finite or countably infinite. Hence if you are able to count the set of items, then the variable is said to be discrete. Definition of Continuous VariableContinuous variable, as the name suggest is a random variable that assumes all the possible values in a continuum. Simply put, it can take any value within the given range. So, if a variable can take an infinite and uncountable set of values, then the variable is referred as a continuous variable. A continuous variable is one that is defined over an interval of values, meaning that it can suppose any values in between the minimum and maximum value. It can be understood as the function for the interval and for each function, the range for the variable may vary.
The difference between discrete and continuous variable can be drawn clearly on the following grounds:
ExamplesDiscrete Variable
Continuous Variable
ConclusionBy and large, both discrete and continuous variable can be qualitative and quantitative. However, these two statistical terms are diametrically opposite to one another in the sense that the discrete variable is the variable with the well-defined number of permitted values whereas a continuous variable is a variable that can contain all the possible values between two numbers. What is the standard form of x²+x-4 = 0 ? Which of the following is not a polynomial function? Standard form of 3x - 10 = 6 write each quadratic equation in the standard form then identify the values of a, b and c(2x + 5) (x + 7) = 0(2x + 7) (x - 5) = 04x(x - 3) = 8 Solve the following by completing the square Solve x²-8x+15=0 guys pa help naman pa sagutan po plss diko kasi magets What is the GCF of 16x and 4xa. 16xb. xc. 4x Give the product of the squares: (x² - 2)² a. x² + 4x + 4b. x² + 2x + 4c. x² - 2x + 4d. x² - 4x + 4 2z³ - z + 6 from z³ + 4z³+ 1 2x²- 7x - 10 from x²-12 -4w+7 from -7w-95n²- 3n from -7n² -n+2may kasama po Sana solution salamat agad What is the product of x²(x − 3)?a. x³ - 3b. x² - 3² c. x³ - 3x² d. x² -3 |