The probability mass function and the cumulative distribution function formulas of a geometric distribution are given below: PMF: P (X = x) = (1 - p) x - 1 p. CDF: P (X ≤ x) = 1 - (1 - p) x. In addition, the following are the geometric probability formulas for mean, variance, and standard deviation. Mean (or) Expected value = 1/p.
1. Majority of Z scores in a right skewed distribution are negative. 2. In skewed distributions the Z score of the mean might be different than 0. 3. For a normal distribution, IQR is less than 2 x SD. 4. Z scores are helpful for determining how unusual a data point is compared to the rest of the data in the distribution. Practice
Note: The empirical rule is only true for approximately normal distributions. Example 2.4.1 2.4. 1: Using the Empirical Rule. Suppose that your class took a test and the mean score was 75% and the standard deviation was 5%. If the test scores follow an approximately normal distribution, answer the following questions:
Future posts will cover other types of probability distributions. We are going over the normal distribution first, because it is a very common and important distribution, and it is frequently used in many data science activities. Let's go a bit deeper into the mathematics used with the normal distribution.. 635 68 369 640 501 150 206 521