when you multiply it by 2, then you get the wrong answer then you just go play black ops 2
Suppose you could call it the Gaussian Distribution or the Laplace-Gauss (not to be confused with the Laplace distribution which takes an absolute difference from the mean rather than a squared error)... however the Brits had no one to name this distribution after (not the German and French names) and because it is the ubiquitous distribution they just called it... well the NORMAL!!
A distribution or set of observations is said to be skewed right or positively skewed if it has a longer "tail" of numbers on the right. The mass of the distribution is more towards the left of the figure rather than the middle.
A histogram consists of bars that are adjacent to each other to represent continuous data in intervals or "bins." This design emphasizes the distribution of data points across the range of values, indicating how frequently each range occurs. The closeness of the bars visually reinforces the idea that the data is part of a continuous spectrum, rather than discrete categories. This helps in understanding patterns, trends, and the overall shape of the data distribution.
They can't. If they are ME, then if you get one, you know that the other will not occur. By def of Indep. , knowing the outcome of an event cannot tell you info about the other. Actually, that is not entirely true - in the (rather trivial) case that the probability of one event is zero - both conditions are met. It is false
Your question is not clear, but I will attempt to interpret it as best I can. When you first learn about probability, you are taught to list out the possible outcomes. If all outcomes are equally probable, then the probability is easy to calculate. Probability distributions are functions which provide probabilities of events or outcomes. A probability distribution may be discrete or continuous. The range of both must cover all possible outcomes. In the discrete distribution, the sum of probabilities must add to 1 and in the continuous distribtion, the area under the curve must sum to 1. In both the discrete and continuous distributions, a range (or domain) can be described without a listing of all possible outcomes. For example, the domain of the normal distribution (a continuous distribution is minus infinity to positive infinity. The domain for the Poisson distribution (a discrete distribution) is 0 to infinity. You will learn in math that certain series can have infinite number of terms, yet have finite results. Thus, a probability distribution can have an infinite number of events and sum to 1. For a continuous distribution, the probability of an event are stated as a range, for example, the probability of a phone call is between 4 to 10 minutes is 10% or probability of a phone call greater than 10 minutes is 60%, rather than as a single event.
Odor is an intensive property. It does not depend on the amount or size of a sample, but rather on the specific identity of the substance.
Elasticity is an intensive property because it does not depend on the amount of the material being considered, but rather on its intrinsic physical characteristics. It remains constant regardless of the size or quantity of the material.
Density is an intensive rather than extensive property.
The distribution of a ransom is a criminal rather then environmental activity.
The word itself is intensive. An intensive pronoun is used to emphasize a preceding noun or pronoun, while a reflexive pronoun is used when the subject and object of a sentence are the same. "Itself" does not refer back to the subject of the sentence, but rather intensifies or emphasizes the noun or pronoun it is attached to.
Intensive labor force could put more emphasis on quality, whereas a ton of intense machinery would just do, do, do without any regard to quality that was not programmed into it.
Photoshop is more CPU intensive than GPU intensive. This means that the performance of Photoshop is more dependent on the power and speed of the computer's central processing unit (CPU) rather than the graphics processing unit (GPU).
Labor-intensive refers to a production process that relies more on human labor than machinery or technology, while capital-intensive refers to a process that relies heavily on machinery, equipment, or capital investment rather than on labor. Labor-intensive industries require more manual work and intensive supervision, while capital-intensive industries involve larger investments in equipment and technology.
Empirical Distribution: based on measurements that are actually taken on a variable. Theoretical Distribution: not constructed on measurements but rather by making assumptions and representing these assumptions mathematically.
Temperature is an intensive property, meaning it does not depend on the size or amount of the substance, but rather represents a specific characteristic of the substance at a given moment in time.
The sentence "I myself will cook dinner tonight" is intensive, as the pronoun "myself" is used to emphasize the subject "I" rather than to indicate that the subject is performing an action on itself.
Exclusive is rather an unusual way to define an integer range! 125 - 74 - 1 = 50.