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.
Because the supply curve basically is for the short run, and not permanent for the long run. That's why it's considered normal.
because the ordinary demand curve ignores the income effect of price changes.also since the compensated demand curve is less inelastic than an ordinary demand curve.
In normal circumstances, ceteris paribus, the supply curve shifts left as competition drives down prices.
Yes, an increase or decrease in income will cause a shift in the demand curve right or left depending on if the good is inferior, normal, or superior
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.
Symmetric
the shape of the curve skewed is "right"
No.
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'.
No.
No, as you said it is right skewed.
It is not at all skewed. As to oddly shaped, it depends on your expectations.
Yes, when a curve is pulled upward by extreme high scores, it is said to be positively skewed. In a positively skewed distribution, the tail on the right side is longer or fatter, indicating that there are a few unusually high values that affect the overall shape of the distribution. This results in the mean being greater than the median.
A distribution that is NOT normal. Most of the time, it refers to skewed distributions.
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.