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    DATA ANALYSIS

                      Data analysis is the process of examining data to understand what it means. It helps you make
                      better decisions by extracting useful information from data.

                      When you visualise data, it helps your brain quickly spot patterns and trends, making it easier to
                      understand the bigger picture. But data analysis goes a step further by using tools like computers
                      and mathematics to look deeper into the data for more detailed insights. After you visualise the
                      data, you can analyse it further to gain a better understanding.

                      Precision, Accuracy and Valid Data

                      When working with data, it’s important to understand precision and accuracy.

                      Precision refers to how detailed or exact a measurement is. Imagine an AI model that predicts
                      the price of a product. If the model gives you a price of `1000.50 every time you run it, the
                      predictions are precise because they are consistent. However, if the actual price is `1080.00,
                      then the model’s predictions are precise but not accurate.

                      Accuracy refers to how close your measurement is to the actual or true value. If an AI system
                      predicts the price of a product as `1800.05, which is very close to the true price of `1800.00, the
                      prediction is accurate because it’s nearly the same as the true value, even if it’s not exactly the
                      same.

                      Let’s use an example of measuring the length of a pencil, to understand precision, accuracy and
                      valid data:

                       Precision: You measure the pencil’s length using an AI-based sensor three times and each
                         time you get the measurement of 7.5 cm. The measurements are precise because they are
                         consistent. But if the actual length of the pencil is 8 cm, your measurement is precise but not
                         accurate.

                       Accuracy: If the pencil’s actual length is 8 cm and you measure it to be 7.9 cm with the AI
                         model, then the measurement is accurate because it’s close to the true value, even if it’s not
                         exactly the same.

                      Valid data is both accurate and precise. In the case of AI models, valid data would mean that
                      the model gives consistent and correct results. For your analysis and conclusions to be correct,
                      you need valid data.
                                                                                                     fact bits
                      Loss of Precision in Digital Data                                        In 1962, statistician John

                      Sometimes, when data is processed by computers, the precision           Tukey defined data analysis
                      of the data can be lost. This is called loss of precision. Let us       in his paper “The Future of
                      understand it from the example:                                          Data Analysis.” His work
                                                                                              helped shape how we use
                       A  number might  originally  be  recorded  as  25, but                  data analysis today.
                         after processing by an AI algorithm, it  might  appear  as
                         25.000000.

                      60         Artificial Intelligence (CT & AI)-VII

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