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There is no particular meaning associated with theta - it will depend on the context.

Q: What does theta mean in normal distribution?

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The mean of a standard normal distribution is 0.

A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.

The standard normal distribution has mean 0 and variance 1. It is not clear what 0.62 has to do with the distribution.

The standard normal distribution is a special case normal distribution, which has a mean of zero and a standard deviation of one.

The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.

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le standard normal distribution is a normal distribution who has mean 0 and variance 1

The standard normal distribution is a normal distribution with mean 0 and variance 1.

The mean of a standard normal distribution is 0.

The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.

A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.

In a normal distribution half (50%) of the distribution falls below (to the left of) the mean.

The standard normal distribution has a mean of 0 and a standard deviation of 1.

The normal distribution can have any real number as mean and any positive number as variance. The mean of the standard normal distribution is 0 and its variance is 1.

The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.

Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"

In the normal distribution, the mean and median coincide, and 50% of the data are below the mean.

In statistics, θ, the lowercase Greek letter 'theta', is the usual name for a (vector of) parameter(s) of some general probability distribution. A common problem is to find the value(s) of theta. Notice that there isn't any meaning in naming a parameter this way. We might as well call it anything else. In fact, a lot of distributions have parameters which are usually given other names. For example, it is common use to name the the mean and deviation of the normal distribution μ (read: 'mu') and deviation σ ('sigma'), respectively.