Q: In Statistics a bell shaped curve is said to be?

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All statistics are data because all statistics are formed of numbers and numbers are a type of data (numrical). But not all data is statistics because not all data is numbers, it can also be words, pictures etc. It's like saying all apples are fruit but all fruit are not apples.

That depends on your teacher's or schools practice. If they "grade on a curve" then all the tests taken will be distributed on a Gaussian bell probability curve. So if you are the only one who missed 4 questions and everybody else missed more you will get the highest grade; but of you are the only one who missed 4 questions and everybody else mised fewer, then you will get the lowest grade. In my school only a few teachers graded on a curve; most would have given a B for missing 4 out of 26 equally important questions. UH UH!If you missed 4 out of 26, you would still get a A-.I aked my teacher and she said yes.

Two objects having both the same size and shaped could be said to be 'congruent'.

The man (or woman) can be said to model a bust, for instance, using clay. Or sculpture if working in stone, marble, plaster, etc.

A normal distribution is not skewed. Skewness is a measure of how the distribution has been pulled away from the normal.A feature of a distribution is the extent to which it is symmetric.A perfectly normal curve is symmetric - both sides of the distribution would exactly correspond if the figure was folded across its median point.It is said to be skewed if the distribution is lop-sided.The word, skew, comes from derivations associated with avoiding, running away, turning away from the norm.So skewed to the right, or positively skewed, can be thought of as grabbing the positive end of the bell curve and dragging it to the right, or positive, direction to give it a long tail in the positive direction, with most of the data still concentrated on the left.Then skewed to the left, or negatively skewed, can be thought of as grabbing the negative end of the bell curve and dragging it to the left, or negative, direction to give it a long tail in the negative direction, with most of the data still bunched together on the right.Warning: A number of textbooks are not correct in their use of the term 'skew' in relation to skewed distributions, especially when describing 'skewed to the right' or 'skewed to the left'.

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