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