Applied Probability and Statistics in Data Analytics class DISCUSSION

QUESTION #1:

A number of organizations are considered data privacy “champions”. You can see the list of organizations here:

- For this exercise, research one of these organizations and describe whether that organization should be considered a data privacy “champion.”
- As a follow-on question, describe how this organization respect for human dignity through data privacy.

**DISCUSSION QUESTION #2:**

Describe the Normal Distribution, Binomial Distribution, and Poisson Distribution. What’s the difference between these distributions? Provide examples in your discussion.

The student will research the probability distribution of Normal Distribution, Binomial Distribution, and Poisson Distribution.

- Research the difference between continuous probability distribution and discrete probability distribution.
- Describe the property of Normal Distribution, Binomial Distribution, and Poisson Distribution.
- Discuss the different situations of how to choose the right probability distribution.

**DISCUSSION QUESTION #3:**

What are the main differences between the Z test and t test? When is the one used over the other?

Students can work through the following steps to finish this essay:

- Research the fundamental concept and the hypothesis of using a Z test and t test.
- Research the use case and sample size of the Z test and t test.
- Research the difference between Z distribution and t distribution.
- Research the calculation of the Z score and t score.

**DISCUSSION QUESTION #4:**

What are the main differences between the chi-square test and ANOVA? When is the one used over the other? What are the steps of conducting the chi-square test and ANOVA?

Students can work through the following steps to finish this essay:

- Research the fundamental concept and the hypothesis of using the chi-square test and ANOVA.
- Research the use case of the chi-square test and ANOVA.
- Research the steps of conducting chi-square test and ANOVA.

**DISCUSSION QUESTION #5:**

Discuss some popular predictive analytics models that are used for regression problems and classification problems. Provide examples and describe how these models solve real-industry problems.

Students can work through the following steps to finish this essay:

- Students will describe the popular predictive models including regression models and classification models.
- Students will research the applications of predictive models in industries.
- Students need to illustrate an example of how the predictive model solve an industry problem.