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5.  Good data has information scattered.                                                      ……….……
                    6.  Highest level of understanding involves critical thinking to interpret data and make good consistent decisions.   ……….……
                    7.  Accurate data closely reflects actual values with  errors.                                ……….……
                    8.  Data interpretation involves collecting the data.                                         ……….……

                 D.  Match the following:
                    1.  Computer Vision                                        a.  Data scraping
                    2.  NLP                                                    b.  Image Data
                    3.  Textual Data                                           c.  Dataset search
                    4.  Sources of data                                        d.  Data history
                    5.  Data Discovery                                         e.  Qualitative Data


                                                  SECTION B (Subjective Type Questions)

                 A.  Short answer type questions:
                    1.  Image of a data pyramid is given here. Based on it, answer the following questions:
                        i.   What is a data pyramid?                                                          A
                       ii.   Name the areas marked as A, B, C, and D in the data pyramid.                     B
                       iii.  Give one important feature of each level.
                    2.  Why is data literacy essential? List any two factors.                                 C
                    3.  How can pie charts be useful in data presentation?                                    D
                    4.  How does informed decision-making benefit from data interpretation?
                    5.  What is the difference between qualitative and quantitative data?
                    6.  What is the purpose of data processing?
                    7.  What is Kaggle and how can it be useful for data enthusiasts?
                    8.  Define the term "Data Backup".
                    9.  Why is the data literacy framework an iterative process?
                    10.  Give any two best practices that can help you ensure data privacy.

                 B.  Long answer type questions:
                    1.  What are the ethical concerns while doing data acquisition?
                    2.  Why is data security important?
                    3.  How is data security related to AI?
                    4.  List any three best practices of cyber security.
                    5.  Explain with example the two types of numeric data.
                    6.  Explain in short the types of data used in three domains of AI.
                                                                                   #Problem Solving & Logical Reasoning
                 C.  Competency-based/Application-based questions:
                      The following dataset represents the students' academic performance, identify which features in the dataset would be
                    considered independent variables and which would be dependent variables in predicting students' final exam grade.

                        Stud Name Study Hours   Attendance   Previous Grades Extracurricular Activity  Final Exam Grade
                        Aarav          5          Yes           B            Sports                   A
                        Riya           7          Yes           A            Debate Club              B
                        Arjun          6          No            C            Music Club               C
                        Ishan          4          Yes           B            Drama Club               B
                        Anaya          8          Yes           A            None                     A







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