That depends on the rules that define the random variable.
In all likelihood, it stands for Probability. For example, Pr(X < 3) is a way of writing "Probability that a random variable, X, takes a value less than 3".
The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.
False. It is approximately 1. Theoretically, it is not 1. I used excel, and I know the probability is between 0.999999 and 1. as the probability of Z<6 is 0.999999. I can't calculate the probability exactly because excel only goes to 7 place accuracy.
If this is an inequality (6 is less than x, or 6 < x), then x is an integer or other value greater than 6.---The variable statement "6 less than x" is (x - 6)This is a value (variable and constant) where the value of x is determined by an equationsuch as x-6 = 4 (x is positive 2) or y = x-6 (y is 6 less than x).
If the cumulative relative frequency when the variable X takes the value x, it means that 0.4 (or 40%) of the values of the variable X are less than or equal to x.
The probability of a random variable being at or below a certain value is defined as the cumulative distribution function (CDF) of the variable. The CDF gives the probability that the variable takes on a value less than or equal to a given value.
For a discrete variable, you add together the probabilities of all values of the random variable less than or equal to the specified number. For a continuous variable it the integral of the probability distribution function up to the specified value. Often these values may be calculated or tabulated as cumulative probability distributions.
In all likelihood, it stands for Probability. For example, Pr(X < 3) is a way of writing "Probability that a random variable, X, takes a value less than 3".
The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.
The rejection region for a hypothesis is the set of values such that if the null hypothesis is true, then the probability of observing a value for the test statistic (the z-score) for a random variable that may be assumed to have a Normal distribution, is at least as great as the value actually observed is less than by chance. The latter is an arbitrarily selected value called the p-value - often 5% or 1%.Note that z-scores may be used only if the random variable is approximately Normally distributed - not otherwise.
0.553
For ungrouped data, the graph for a random variable (rv), X, is usually a line graph whose horizontal axis is the values that the random variable can take, and whose vertical axis is the number of observations (or outcomes) of the random variable that are less than or equal to that value of the rv. For grouped data the graph is usually a corresponding bar graph.
False. It is approximately 1. Theoretically, it is not 1. I used excel, and I know the probability is between 0.999999 and 1. as the probability of Z<6 is 0.999999. I can't calculate the probability exactly because excel only goes to 7 place accuracy.
No. Probability must be between 0 and 1.
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.
As the maximum value of the dots on the face of a traditional dice is 6 the probability of throwing A die with the value of less than 7 is 100%.
The unknown value of the variable could be greater, less or even equal to 12.50