Reference no: EM131670636
Discussion
This discussion for this week was a little hard for me, so if the answers that is given is incorrect, please feel free to correct me since math is not my best subject. After stating all of the problems I have with Math, here are the answers to the questions for this week discussion.
1. To what shape of the histogram converge when you roll 1 die at a time?
"If only one die is rolled, the histogram should look flat" (J.S.E., 1998).
1. What happens when you roll a pair of dice?
"For two dice, the histogram should look like the top of a witch's hat" (J.S.E., 1998).
1. When you roll 3 dice? 4 dice? 5 dice?
"For three or more dice, the histogram will be more bell-shaped" (J.S.E., 1998).
1. Discuss a normal distribution and what it implies.
"The normal distribution is not only a symmetrical, but bell-shaped, a shape that (Loosely) suggests the profile of a bell. Being bell-shapes means that most values of the continuous variable will cluster around the mean. Although the values in a normal distribution can range from negative infinity to positive infinity, the shape of the normal distribution makes it very unlikely that extremely large or extremely small values will occur" (Levine, Stephen, and Szabat, P. 190, 2017).
1. Are there other distribution patterns?
The other distribution pattern that I found was similar is the skew normal distribution.
" The skew normal has a number of interesting properties related to alpha:
1. If the skew normal has a skew of zero, then it becomes the normal distribution.
2. If the sign of alpha changes, the distribution will flip over the y-axis.
3. As alpha increases (in absolute value), the skew also increases.
4. As alpha tends towards infinity, the series converges to the folded normal density function.
Therefore, the normal distribution can be seen as a special case of the skew normal distribution" (Statistics How To, 2017)
Levine, D. M., Szabat, K.A., & Stephan, D. (2017). Statistics for managers using Microsoft Excel. Boston: Pearson.