September 10, 2020 News
 1.   Online Credit: Groups C, D and E will present their solutions (prepare a slide (or two)) 
      during the Tu.,Sept. 15 lecture. 
 2.   Start working on Task1 of ProblemSet1, if you have not already started. 
 3.   The lectures on Sept. 10+15+17 will discuss a mixture of topics: EDA, Classification, 
      Kritik&Peer Evaluation and ProblemSet1
 4.   Today’s mode of operation: Unmute microphone&ask question today; only when 
      asked!!!; will have additional Q&A near the end of the lecture
 5.   Today’s Lecture
      a.  Finish EDA Slide Set (mostly)
      b.  Useful Source Code for ProblemSet1
      c.  Watch Kritik Video online (6 minutes) and Brief Discussion of the Content 
      d.  Discussion of an Example Rubric 
      e.  Starting new topic: Classification Centering on “Classification Basics” and DT, 
          SVM, k-NN and NN 
 Tan,Steinbach, Kumar: Exploratory Data Analysis (with major  modifications and additions by Ch. Eick)                             9/9/2020
                         Rubric
    In education terminology, rubric means "a 
    scoring guide used to evaluate the quality of 
    students' constructed responses". Put simply, 
    it is a set of criteria for grading assignments. 
    Rubrics usually contain evaluative criteria, 
    quality definitions for those criteria at 
    particular levels of achievement, and a 
    scoring strategy. They are often presented in 
    table format and can be used by teachers 
    when marking, and by students when 
    planning their work. (from Wikipedia)
 Tan,Steinbach, Kumar: Exploratory Data Analysis (with major  modifications and additions by Ch. Eick)                             9/9/2020
     Kritik Activity Stages
                                         Stage 1: Create → Follow the 
    Stage                                instructions, read the provided 
    1                                    rubric and create a submission
                                         Stage 2: Evaluate → Anonymously 
                                         score your peers based on a rubric, 
                                         and give a provide written 
  Stage                        Stage     comments (2 components: score + 
  2                            3         justification)
                                         Stage 3: Feedback → Provide peer 
                                         evaluators anonymous feedback on 
                                         how motivational/critical their 
                                         comments were
                                                                        4
                                        Novel: Everything that is in yellow!!
 Tan,Steinbach, Kumar: Exploratory Data Analysis (with major  modifications and additions by Ch. Eick)                             9/9/2020
          Exploratory Data Analysis
     Remark: covers Chapter 3 of the first edition Tan book in 
         Part
     Organization
     1. Why Exploratory Data Analysis?
     2. Summary Statistics
     3. Visualization
 Tan,Steinbach, Kumar: Exploratory Data Analysis (with major  modifications and additions by Ch. Eick)                             9/9/2020
     1. Why Data Exploration?
     A preliminary exploration of the data to better 
     understand its characteristics.
    Key motivations of data exploration include
       – Getting a better understanding of the data
       – Create background knowledge about the data to be analyzed
       – Helping to select the right tool for preprocessing, data analysis and data 
          mining
       – Making use of humans’ abilities to recognize patterns
           People can recognize patterns not captured by data analysis tools 
    Related to the area of Exploratory Data Analysis (EDA)
       – Created by statistician John Tukey
       – Seminal book is Exploratory Data Analysis by Tukey
       – A nice online introduction can be found in Chapter 1 of the NIST 
          Engineering Statistics Handbook
       http://www.itl.nist.gov/div898/handbook/index.htm
 Tan,Steinbach, Kumar: Exploratory Data Analysis (with major  modifications and additions by Ch. Eick)                             9/9/2020