A(n)_distribution has a "bell" shape.

Quesiton : A(n)_distribution has a "bell" shape.

Answer: What are some advantages of a dotplot over a frequency polygon

A(n)_distribution has a "bell" shape. A _ histogram has the same shape and horizontal scale as a histogram but the vertical scale is marked with relative frequencies instead of actual frequency. normal A(n)_distribution has a "bell" shape. A _ histogram has the same shape and horizontal scale as a histogram but the vertical scale is marked with relative frequencies instead of actual frequency. relative frequency A(n) _distribution has a "bell" sh ape. The Empirical Rule is an approximation that applies only to data sets with a bell - shaped relative frequency histogram. It estimates the proportion of the measurements that lie within one two and three standard deviations of the mean. a specific bell - shaped frequency distribution commonly assumed by statisticians to represent the infinite population of measurements from which a sample has been drawn; characterized by two parameters the mean (x) and the standard deviation (σ) in … Bell-shaped distribution 6. 2 7 Determining the Mean and Median The Mean ... n xi 2 Bell - shaped distributions • Measurements that have a bell - shape are so common in nature that they are said to have a normal distribution. • … The term bell curve is used to describe the mathematical concept called normal distribution sometimes referred to as Gaussian distribution. ‘ Bell curve’ refers to the shape that is created when a line is plotted using the data points for an item that meets the criteria of ‘normal distribution’. Show transcribed image text If a distribution has a bell-sha ped distribution with mean 100 and standard deviation 15 what fraction of the values are greater than 100? 0.5 0.4 0.25 0.35 1 If a distribution has a bell-sha ped distribution with mean 100 and standard deviation 15 approximately what fraction of the values are between 70 and 100? It seems you have been told to think of " bell - shaped " data - symmetric data that peaks in the middle and which has lower probability in the tails - as "normal". But the normal distribution requires a specific shape to its peak and tails. Bell - shaped but being too narrow in the middle will have a different kind of kink in the center (kinks up then back down). Being not quite symmetric means one of the tails will kink. Use the "fat pencil" test. Do the prob plot then put a pencil on the line. If points start trending off that pencil your data isn't normally distributed. A normal distribution is projected as a bell shaped distribution with the area can be symmetrically divided into two. In this case the problem says non-symmetric districution which would have to be a skewed distribution. Carl Friedrich Gauss Ronald Fisher Francis Galton Poisson distribution Binomial distribution Probability distribution