Please submit a minimum 1 page (single spaced) . Based on your Module topics, what did you find new and interesting? And what appeared to be a review? Also, identify at least one discussion post you found interesting, helpful, or beneficial (and why).

## Overview & Learning Objectives

**Topics covered in this Module**

- Cluster analysis
- K-means clustering
- Association rules
- Text Mining
- Word clouds
- Statistical inference
- Selecting a sample
- Point estimation
- Sampling distributions
- Interval estimation
- Hypothesis tests
- Big data
- Sampling error

**Learning Objectives**

By the end of this module, students should be able to:

- Explain concepts:
- cluster analysis
- centroids linkage
- k-means clustering

- Describe association rules and market basket applications
- Explain word clouds
- Discuss text mining and unstructured data
- Apply k-means clustering
- Compute cluster centers
- Calculate confidence intervals using Excel
- Calculate descriptive statistics using the Data Analysis Toolpak in Excel
- Conduct one-tailed and two-tailed hypothesis tests in Excel
- Calculate p-values and determine whether the null hypothesis should be rejected