Data Mining and Analytics Software Solutions Review Questions
Explore review questions on data mining and analytics software packages like IBM SPSS, SAS Enterprise Miner, and more. Understand the differences between conventional statistics and data mining, as well as the benefits of using programming for automation and auditing.
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Presentation Transcript
Week 1: Ungraded review questions
Can you explain your answer? Use your fingers to indicate your answer: 1=A, 2=B, 3=C, 4=D. For check all that apply, use your both hands. After viewing the question, show me your answer in 15 seconds. Next, turn to your neighbor and you have one minute to convince him/her that you are right.
Which software package(s) below are specifically developed for data mining/big data analytics? (Check all that apply) A. IBM SPSS Statistics B. SAS Enterprise Guide C. SAS Enterprise Miner D. IBM SPSS Modeler
What is/are the difference(s) between conventional statistics and data mining? (Check all that apply) A. Conventional statistical procedures are built for relatively small samples whereas data mining is good for big data analytics. Traditional procedures aim to test a pre- determined hypothesis while data mining focuses on recognizing data patterns. Classical procedures require many assumptions but data mining is more flexible All of the above B. C. D.
Which software package(s) below is/are run through the Internet (using a remote server to perform data analysis)? A. IBM SPSS Modeler B. IBM SPSS Statistics C. SAS on Demand D. SAS University Edition
Which software package(s) below provide graphical user interface (GUI) to minimize typing? A. SAS Programming Environment B. SAS Studio C. SAS Enterprise Guide D. JMP Pro
Which software package(s) include AMOS for structural equation modeling (SEM)? A. IBM SPSS Base B. IBM SPSS Standard C. IBM SPSS Premium D. All of the above
Graphical user interface (e.g. point and click, drag and drop) is very easy. Why do we need programming (typing the syntax)? A. Programming can automate routine, repetitive, and tedious tasks. B. When every step is written down, there is an audit trail. It makes debugging and documentation much easier. C. Programs can be used as templates. For similar tasks we can edit existing programs. D. All of the above
Psychology is about understanding and helping people. Why do I need to devote so many efforts in data science? A. Because I need data-driven decisions instead of counting on ideology or subjective opinions. B. Because the skill of data analysis could open doors to graduate assistantship and other job opportunities. C. Data science is fun! I feel good when I can face challenges and suucced. D. All of the above
