![]() “Normality” refers to the normal distribution, so an estimator that is asymptotically normal will have an approximately normal distribution as the sample size gets infinitely large. “Asymptotic” refers to how an estimator behaves as the sample size gets larger (i.e. The uniform probability distribution is symmetric about the mean and median. ![]() Which term defines the normal curve gets closer and closer to the horizontal axis but never touches it?Īsymptotic means that the normal curve gets closer and closer to the X-axis but never actually touches it. The normal distribution is often called the bell curve because the graph of its probability density looks like a bell. The normal distribution is a continuous probability distribution that is symmetrical on both sides of the mean, so the right side of the center is a mirror image of the left side. Why is the bell curve used to represent the normal distribution Why not a different shape? It is the horizontal scale of a standard normal distribution. A z-score is a measure of position that indicates the number of standard deviations a data value lies from the mean. ![]() What does the horizontal scale represent in standard normal distribution?Ī z-score (or standard score) represents the number of standard deviations a given value x falls from the mean, μ. The two tails of the normal probability distribution extend indefinitely and never touch the horizontal axis. ![]() (The curve never crosses the x-axis.) Which tail of the normal distribution extend indefinitely never touching the horizontal axis?Ĭharacteristics (Graph) of Normal Probability Distribution: For a normal probability distribution, mean median and mode all are equal. 8 Is the normal distribution symmetric about the mean?ĭoes a normal curve intersect the horizontal axis?Įach normal distribution is defined by µ (mean) and σ (standard deviation σ determines the sharpness or flatness of the curve).7 Why does the distribution curve never touch the x axis?.6 What is the difference between the normal distribution and standard normal distribution?.5 What does the normal curve touch when it is asymptotic?.3 Which term defines the normal curve gets closer and closer to the horizontal axis but never touches it?.2 Which tail of the normal distribution extend indefinitely never touching the horizontal axis?.1 Does a normal curve intersect the horizontal axis?.The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities. As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L (it is only valid within the Boolean subalgebras of L). The orthocomplemented modular lattice of subspaces L, of a quantum system with d-dimensional Hilbert space H(d), is considered.
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