Basics of ML & AL Week 2 Challenge

2. While the simple mean (sum of observations divided by the number of observations) is common measure of central tendency, expected value offers a distinct perspective, particularly when dealing with probability distributions.

In conclusion, while the simple mean is a useful tool for summarizing a dataset, expected value provides a theoretical framework for understanding the long term average outcomes of random variables, making it invaluable in various fields of statistics and decision making.

3. Skewness a measure of the asymmetry in a probability distribution can significantly influence the interpretation data. While it's often considered undesirable, it's not inherently bad and can provide valuable insights.

When Skewness is a Concern

Statistical tests : Many statistical tests are based on the assumption of normality. If the data is significantly skewed , these test might not be appropriate.

Data interpretation : Skewness can make difficult to interpret the meaning of the mean and standard deviation. In such cases, other measure like the median and interquartile range might be more informative.

In conclusion, while skewness is often considered challenge, it's essential to recognize that it can provide valuable insights into the data. By understanding the implications of skewness and choosing appropriate statistical methods, analysts can draw more accurate and meaningful conclusions from their data.

4. a) z= 711-680/31 = 1.00

b) z = 740-680/31 = 1.93

c) z = 700-680/31 = 0.641

d) for continuous distribution, the probability of a single point is always 0. This is because there are infinitely many points within any interval, and the probability of any specific point is infinitesimally small.

P (X=720)=0