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 clusteringDescribe 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
Camm_4e_Ch05_PPT-Module3Reflection.pptx
Camm_4e_Ch06_PPT-Module3reflection2.pptx
