Answer this question...similarities and differences between normal curve and skewness
Left Right Symmetric
The standard normal curve is symmetrical.
It is a normal curve with mean = 0 and variance = 1.
the standard normal curve 2
A bell shaped probability distribution curve is NOT necessarily a normal distribution.
A normal curve, also known as a bell curve, is symmetric around its mean, indicating that data points are evenly distributed on either side, with most values clustering around the center. In contrast, a skewed curve is asymmetrical, meaning that it has a tail extending more to one side than the other; in a positively skewed curve, the tail is on the right, while in a negatively skewed curve, it is on the left. This skewness affects the mean, median, and mode of the data distribution, leading to different interpretations of the data's central tendency.
Left Right Symmetric
A positive skewness is when the value of mean is greater than the mode. that is, the curve is more skewed at the right hand side or the right tail is longer than the left tail. The negative skewness is when the mean is smaller than the mode, and in this case the curve is more skewed on the left hand side.
The standard normal curve is symmetrical.
No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.
It is a normal curve with mean = 0 and variance = 1.
the standard normal curve 2
No
The area under the standard normal curve is 1.
There is no such thing as an "ormal curve". And a Normal curve IS symmetrical!
The area under the normal curve is ALWAYS 1.
Ah, the Pearson Coefficient of Skewness, fancy term for measuring the asymmetry of a probability distribution. It tells you if your data is skewed to the left, right, or if it's all hunky-dory symmetrical. Just plug in your numbers, crunch some math, and voila, you'll know how wonky your data is. Just remember, skewness doesn't lie, so embrace those skewed curves!