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What is normal distribution in statstics?
The normal distribution is a statistical distribution. Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights. The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution. Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable. These characteristics make the normal distribution very important in statistics. See attached link for more.
What distribution does the F distribution approach as the sample size increases?
The F distribution is used to test whether two population variances are the same. The sampled populations must follow the normal distribution. Therefore, as the sample size increases, the F distribution approaches the normal distribution.
When you replace each variable with a number and then follow order of operations is called what?
Evaluate
When does normal distribution occur?
The normal distribution occurs when a number of random variables, with independent distributions, are added together. No matter what the underlying probability distribution of the individual variables, their sum tends to the normal as their number increases. Many everyday measures are composed of the sums of small components and so they follow the normal distribution.
How do you put a polynomial in standard form?
For a polynomial in a single variable you start with the term containing the highest power of that variable and then follow with the next highest power and so on. For polynomials is several variables, you first group them by the sum of the powers of all the variables (remember that y is y^1). Then, you order each group by the power of one variable, then another variable and so on.
How you induce the poisson distribution in normal queuing method?
I have no idea what you mean by inducing a distribution.If you assume that the number of events - people joining the queue - in a given time interval has a constant average rate and the the events are independent of one another, then arrivals in the queue follow a Poisson distribution.
What is the difference between a random number and random variable?
A random number is also called a random deviate or pseudo random number. It is a value that is generated by a computer, given a probability distribution. The uniform random number is distributed according to the uniform distribution with values from 0 to 1 and is often used to generate other numbers that follow other distributions. The relative frequency plot of random numbers generated using a particular distribution may not be exactly equal to the particular distribution, due to the limited number of points. But, as the number of random deviates increases, the frequency plot will more closely approximate the given distribution. Random variable have both an intuitive and mathematical definitions. Probability theory is based on sets of events. A throw of coin will have certain outcomes. The random variable, X, links or maps these events to values. A coin can come up heads, so the mapped random variable of this outcome can be 0, and for tails, the random variable of this outcome can be 1. The mathematical definition is a bit more complex- see related links. A random variable is associated with what is considered a random process. If we know the outcome without any uncertainty, we would call it an deterministic process and the outcomes deterministic variables.
What is normal distribution in statstics?
The normal distribution is a statistical distribution. Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights. The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution. Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable. These characteristics make the normal distribution very important in statistics. See attached link for more.
What is the difference between multiple regression and logistic regression?
In cases wherethe dependent variable can take any numerical value for a given set of independent variables multiple regression is used.But in cases when the dependent variable is qualitative(dichotomous,polytomous)then logistic regression is used.In Multiple regression the dependent variable is assumed to follow normal distribution but in case of logistic regression the dependent variablefollows bernoulli distribution(if dichotomous) which means it will be only0 or 1.
What were the outcomes of the Islamic Revolution?
For women and men to follow the Islamic religion.
What is the definition of a variable term?
somthing that you can follow a ( formula)
Intelligence scores follow what kind of distribution?
The IQs of a large enough population can be modeled with a Normal Distribution
How do you interpret coefficient of dummy variable?
To interpret the coefficient of a dummy variable is to follow all of the steps of the equation that is being used as if the dummy variable was a real one.
What is it called when you replace a variable with a number and follow order of operations?
Substitution
Will the distribution of the sample means follow the uniform distribution?
The distribution of the sample means will, as the sample size increases, follow the normal distribution. This is true for any given distribution (e.g. does not need to be a normal distribution). This concept is from the central limit theorem. It is one of the most important concepts in statistics, along with the law of large numbers. An applet to help you understand this concept is located at: http:/www.stat.sc.edu/~west/javahtml/CLT.html
What distribution does the F distribution approach as the sample size increases?
The F distribution is used to test whether two population variances are the same. The sampled populations must follow the normal distribution. Therefore, as the sample size increases, the F distribution approaches the normal distribution.
What other types of data might follow a normal distribution?
Those data that were not mentioned in the original answer but which might follow a normal distribution. Since the question does not specify which ones were already listed, it is not possible to say which were "other".
