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Author of the       Weblink to the     How was the situation      Key figures in the
                        Source              Source             described by the Source    source












                   You have to rank the sources of the news articles from most accurate to least, state reasons for your choice.

                           Rank                       Data Source                 Remarks











                   So, we can conclude that every data tells a story, but we must be careful before believing the story.




                         How to Become Data Literate?


                 Data literate is a person who can interact with data to understand the world around them and derive meaningful
                 information from data. Some key points that will help you become a data literate are as follows:

                    • Data identification and sourcing: Identify the source of data to find whether the data is reliable or not.
                    • Understand the basics: Learn the concepts of data, types of data, and how it can be used as not all data is
                   suitable for every kind of analysis.

                    •  Learn data analysis tools: There are many data analysis apps available that can be learned in order to understand
                   the impact of the right data. Analysis involves using statistical tools or software to interpret the data. This can
                   include calculating simple averages for more complex tasks.
                    • Gain statistical knowledge: Statistics play a vital role in data literacy. It's one of the vital components that must
                   be learned before you dive into the data-driven world.
                    •  Use data visualisation: Understand the techniques of data visualisation graphics, and charts. Tools like tableau,
                   matplotlib, and python can be used effectively.

                    •  Learn data manipulation: Understanding how to manipulate data to meet the requirements is also one of the
                   key factors. Methods like filtering, sorting, grouping, and omitting are essential for extracting insights from large
                   dataset.
                    •  Practise data cleaning: Learning to remove data redundancy and data inaccuracy is essential to being data
                   literate. This may include dealing with missing values, removing outliers, or transforming data into a format
                   suitable for analysis.






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