What measurement forms normal distribution? Would it be the mean and variance? (avg. and standard deviation)
Could you help me please
These measurements do not "form" the normal distribution, but give dimensions of the normal distribution (measures of central tendency and variability). These allow you to determine where specific scores fall in the distribution, when you calculate the Z score.
I hope this helps. Thanks for asking.
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Of course! The normal distribution, also known as the Gaussian distribution, is a continuous probability distribution that is symmetrical and bell-shaped. It is defined by two parameters: the mean (μ) and the variance (σ²), or equivalently, the standard deviation (σ).
The mean, often referred to as the average, represents the center or expected value of the distribution. It determines the location of the peak of the bell-shaped curve.
The variance measures the spread or dispersion of the data points around the mean. It accounts for how individual data points deviate from the average value.
The standard deviation is simply the square root of the variance. It provides a more intuitive measure of dispersion, as it is measured in the same units as the original data.
Together, the mean and variance (or standard deviation) fully describe the characteristics of a normal distribution. They determine the shape, location, and dispersion of the data.
To summarize, yes, the mean and variance (or standard deviation) are the key measurements that form a normal distribution.