Computer Base Module 3 – Reflection
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
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