true - Distributions that have the same shape on both sides of the center are called symmetric
Symmetry is when something has exactly the same shape on either side of an axis line. T is a vertical symmetrical shape.
The probability density functions are different in shape and the domain. The domain of the beta distribution is from 0 to 1, while the normal goes from negative infinite to positive infinity. The shape of the normal is always a symmetrical, bell shape with inflection points on either sides of the mean. The beta distribution can be a variety of shapes, symmetrical half circle, inverted (cup up) half circle, or asymmetrical shapes. Normal distribution has many applications in classical hypothesis testing. Beta has many applications in Bayesian analysis. The uniform distribution is considered a specialized case of the beta distribution. See related links.
The frequency distribution is likely to be symmetrical and bell-shaped, resembling a normal distribution. Given that the mean, median, and mode are all equal at 12,000 pounds, it suggests that the data is centered around this value with a balanced spread on either side. This indicates that the distribution has a single peak at the center, with a consistent frequency of values around the mean.
yes it is a symmetrical shape
Asymmetry is when a shape is not symmetrical.
symmetrical
The distribution described is a normal distribution. It is characterized by a symmetric bell-shaped curve where the mean, median, and mode are all equal and located at the center of the distribution.
Symmetry is when something has exactly the same shape on either side of an axis line. T is a vertical symmetrical shape.
It is a symmetrical, "bell-shaped" curve. The tails are infinitely long.
The probability density functions are different in shape and the domain. The domain of the beta distribution is from 0 to 1, while the normal goes from negative infinite to positive infinity. The shape of the normal is always a symmetrical, bell shape with inflection points on either sides of the mean. The beta distribution can be a variety of shapes, symmetrical half circle, inverted (cup up) half circle, or asymmetrical shapes. Normal distribution has many applications in classical hypothesis testing. Beta has many applications in Bayesian analysis. The uniform distribution is considered a specialized case of the beta distribution. See related links.
yes it is a symmetrical shape
False. It can be skewed to the left or right or be symmetrical.
Only objects that have the exact size, shape, mass and density distribution can have the same center of mass. Any variation and the center of gravity would move. Furthermore, only objects that are geometrically symmetrical (think sphere) can have a center of gravity at their geometric center.
CO2 is a nonpolar molecule because it has a linear shape with a symmetrical distribution of its oxygen atoms on either side of the carbon atom. This symmetrical arrangement results in the overall molecule having a net dipole moment of zero, making it nonpolar.
symmetrical in shape, with the carbon atom in the center and the two oxygen atoms on opposite sides. This balanced distribution of charge results in no overall dipole moment, making it nonpolar.
Either can be used for symmetrical distributions. For skewed data, the median may be more a appropriate measure of the central tendency - the "average".
CO2 is a polar molecule because it has a symmetrical linear shape that results in unequal distribution of charge. The other molecules listed are nonpolar because they have symmetrical shapes that result in an even distribution of charge.