Gaussian distribution. Some people refer to the normal distribution as a "bell shaped" curve, but this should be avoided, as there are other bell shaped symmetrical curves which are not normal distributions.
difference between market price and normal price
There is the normal probability density function (pdf) which is given in the attached link. The normal probability cumulative distribution function (cdf) is used to calculate probabilities, and there is no closed form equation for this. Many statistical programs have the cdf built in. Some references are given at the end of the link to find approximate cdf. The cdf, is usually written F(x) and the pdf f(x). F(x) is the integral of f(x) from minus infinity to x.
What is the difference between normal and inferior goods
Normal goods are everyday things that the average person would own. Inferior things are more of a low quality item that is considered for poor people.
There is no such thing. The Normal (or Gaussian) and Binomial are two distributions.
Use the continuity correction when using the normal distribution to approximate a binomial distribution to take into account the binomial is a discrete distribution and the normal distribution is continuous.
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.
The binomial distribution is a discrete probability distribution which describes the number of successes in a sequence of draws from a finite population, with replacement. The hypergeometric distribution is similar except that it deals with draws without replacement. For sufficiently large populations the Normal distribution is a good approximation for both.
The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
The binomial distribution can be approximated with a normal distribution when np > 5 and np(1-p) > 5 where p is the proportion (probability) of success of an event and n is the total number of independent trials.
You can use a normal distribution to approximate a binomial distribution if conditions are met such as n*p and n*q is > or = to 5 & n >30.
A small partial list includes: -normal (or Gaussian) distribution -binomial distribution -Cauchy distribution
The central limit theorem basically states that for any distribution, the distribution of the sample means approaches a normal distribution as the sample size gets larger and larger. This allows us to use the normal distribution as an approximation to binomial, as long as the number of trials times the probability of success is greater than or equal to 5 and if you use the normal distribution as an approximation, you apply the continuity correction factor.