A discrete random variable is one to which a whole number can be associated, that is, those that by their nature do not allow a fractioning of the unit, for example number of siblings, number of heads when toss
Let {eq}X {/eq} be a discrete random variable such that {eq}P(X \leq k) = 1 - \dfrac{k + 2}{2^{k + 1}},\,\,k = 1,2,3,... {/eq} what is {eq}P( X = 3) {/eq}? Distribution Function The Distribution functi...
or an infinite, but countable number of values. The number of patients that have a reduced tumor size in response to a treatment is an example of a discrete random variable that can take on a finite number of values. The number of car accidents...
Explore the IBM library of foundation models in the IBM watsonx portfolio to scale generative AI for your business with confidence. Footnotes 1 "What is prompt tuning?", IBM Research, 15 February 2023. 2 "Machine learning model evaluation", Geeksforgeeks.org, 2022....
When you have a quantitative variable, it can be discrete or continuous. In broad terms, the difference between the two is the following: You count discrete data. You measure continuous data. Discrete variables can only take on specific values that you cannot subdivide. Frequently, discrete data...
A "discrete" random variableisone which can take ononlya countable number of distinct valueslike 0, 1, 2, 3, 4, 5…100, 1 million, etc. Some examples of discrete random variables include: The number of times a coin lands on heads after being flipped 20 times. ...
The range of a distribution with a discrete random variable is the difference between the maximum value and the minimum value. For a distribution with a continuous random variable, the range is the difference between the two extreme points on the distribution curve, where the value of the functi...
Discrete Distribution – This can be applied only when the random variables can be in some limited numbers where the values can be counted. Each possible value is associated with a probability. Discreteprobability distribution functioncan be a poisson distribution, in which shows the occurrence of ...
Discrete Continuous There exist suchprobability distributionsthat can apply only to countable outcomes. Examples include the number of red cards drawn from a deck or the number of defective items in a batch. For each of such countable outcomes, its probability is calculated through what is known ...
With linear regression, one independent variable is used to explain and/or predict the outcome of Y. Multiple regression uses two or more independent variables to predict the outcome. With logistic regression, unknown variables of a discrete variable are predicted based on known value of other ...