0
What else can I help you with?
What are the advantages of using standard normal distribution over the normal distribution?
The standard normal distribution is tabulated. The critical values for various outcomes can therefore be worked out easily from tables. The normal distribution is extremely difficult to integrate: most people, even with a university degree in mathematics will be unable to do so. So working out the probability of events from the normal distribution is near enough impossible.
How do you solve a standard normal distribution?
You do not solve a standard normal distribution. It is not a question nor an equation or inequality to be solved. You can answer questions using the standard normal distribution but what you do depends on the question and on what information is given.
What are the Advantages and disadvantages of normal distribution?
One advantage of using normal distribution is that there are less errors. A disadvantage of normal distribution is that it can not be interpreted to terms of probabilities.
What are advantages and disadvantages of normal distribution?
One advantage of using normal distribution is that there are less errors. A disadvantage of normal distribution is that it can not be interpreted to terms of probabilities.
Do some normal probability distributions have different means and different standard deviations?
Yes. Normal (or Gaussian) distribution are parametric distributions and they are defined by two parameters: the mean and the variance (square of standard deviation). Each pair of these parameters gives rise to a different normal distribution. However, they can all be "re-parametrised" to the standard normal distribution using z-transformations. The standard normal distribution has mean 0 and variance 1.
What are the advantages of using standard normal distribution over the normal distribution?
The standard normal distribution is tabulated. The critical values for various outcomes can therefore be worked out easily from tables. The normal distribution is extremely difficult to integrate: most people, even with a university degree in mathematics will be unable to do so. So working out the probability of events from the normal distribution is near enough impossible.
How do you solve a standard normal distribution?
You do not solve a standard normal distribution. It is not a question nor an equation or inequality to be solved. You can answer questions using the standard normal distribution but what you do depends on the question and on what information is given.
What are the Advantages and disadvantages of normal distribution?
One advantage of using normal distribution is that there are less errors. A disadvantage of normal distribution is that it can not be interpreted to terms of probabilities.
What are advantages and disadvantages of normal distribution?
One advantage of using normal distribution is that there are less errors. A disadvantage of normal distribution is that it can not be interpreted to terms of probabilities.
How the normal distribution could be transformed to a standard normal distribution?
You may transform a normal distribution curve, with, f(x), distributed normally, with mean mu, and standard deviation s, into a standard normal distribution f(z), with mu=0 and s=1, using this transform: z = (x- mu)/s
Do some normal probability distributions have different means and different standard deviations?
Yes. Normal (or Gaussian) distribution are parametric distributions and they are defined by two parameters: the mean and the variance (square of standard deviation). Each pair of these parameters gives rise to a different normal distribution. However, they can all be "re-parametrised" to the standard normal distribution using z-transformations. The standard normal distribution has mean 0 and variance 1.
Using the standard normal distribution find the probability that z is greater than 1.78?
0.0375
What is the probability of P z-0.35 using the standard normal distribution?
p(Z<0.35) - 0.5 = 0.6900
What does the normal allow you to measure?
The normal distribution allows you to measure the distribution of a set of data points. It helps to determine the average (mean) of the data and how spread out the data is (standard deviation). By using the normal distribution, you can make predictions about the likelihood of certain values occurring within the data set.
What is standard deviation stretch?
The standard deviation stretch is used to stretch the output values using a normal distribution. The result of this stretch is similar to what is seen by the human eye.
Why is it necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution?
It is necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution because the normal distribution contains real observations, while the binomial distribution contains integer observations.
Can the unit normal table be used for any normal distribution?
Yes, if you mean normal with a mean other than 0 and/or standard error other than 1. If m is the mean and s the standard error, then transform the original data, y, using: z = (y - m)/s z will have the N(0,1) distribution!!!!!!!
