Page 182 - Ai_V1.0_Class9
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1.  Examine the following datasets:
                    Quantitative Data:
                     Number of petals on a flower:                   Height of flowers (in centimeters):
                     Rose: 32                                        Rose: 45
                     Lily: 24                                        Lily: 55
                     Sunflower: 89                                   Sunflower: 120
                     Tulip: 16                                       Tulip: 30
                     Qualitative Data:
                     Colour of flowers:                            Fragrance intensity:
                     Rose: Red                                     Rose: Strong
                     Lily: White                                   Lily: Mild
                     Sunflower: Yellow                             Sunflower: None
                     Tulip: Pink                                   Tulip: Moderate
                     These datasets contain both quantitative data (number of petals and height) and qualitative data (colour and fragrance
                    intensity) for different types of flowers (Rose, Lily, Sunflower, Tulip).
                     a.  Discuss the differences between quantitative and qualitative data interpretation.

                     b.   Describe the methods and techniques commonly used for interpreting quantitative and qualitative data, highlighting
                       their respective strengths and limitations.
                  2.  You are tasked with analysing the performance of a company's sales across different regions over the past year. How
                    would you utilise data visualisation techniques to present this information effectively to the company's stakeholders
                    during a quarterly review meeting? Describe the types of visualisations you would use and explain how they would help
                    convey the sales trends and patterns to the audience.



                                                                                 #Experiential Learning
                               Lab



                        Ask students to collect data of different coloured objects in the Lab and record it in a spreadsheet. Create a
                        basic bar chart to visualise the collected data using spreadsheet software. Later, ask students to present their
                        bar charts, followed by a brief discussion on the importance of data quality and ethical considerations in AI.


































                    180     Artificial Intelligence Play (Ver 1.0)-IX
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