Topic covid 19 Answer serial-wise with headings

DATA WRANGLING AND EXPLORATORY DATA ANALYSIS Introduction This assessment activity assumes that you have now acquired data that support your business case. This module recognises the data could potentially be in a form that is not suitable for further processing and analysis. Therefore, you will apply appropriate data-wrangling techniques to make your data ready for further processing and analysis. You will also use suitable graphical and non-graphical techniques to perform the exploratory data analysis. Details At this stage, you should have a firm grasp of the way MS Excel works. This activity will be using the MS Excel and PowerQuery features to wrangle the data into a form suitable for further processing and analysis. You will also use visualisation and analytics features in MS Excel to perform exploratory data analysis. Requirements In this part of the assessment, you will apply data wrangling and EDA on the data identified and acquired in the previous stage. The requirements of this part are as follows: Apply appropriate data wrangling techniques to ensure that your data is in a suitable format and data quality issues are rectified, and production quality data is obtained. Not that the wrangling techniques that you may need to apply to vary based on the initial form of the data, how tidy and clean the data is, whether any transformation or conversion is required and so on. Hence, the data may require a small or significant amount of work. Apply EDA including graphical and non-graphical techniques to gain insights about your data, and identify potential relationships and trends, outliers, important variables, etc. This step should enable you to formulate valuable questions about the problem or refine existing questions. For the visual exploration of the data and drawing insights from your analysis, you can use some of the following charts (at least three types) o Bar and pie charts o Histograms and frequency plots o Line graphs o Scatterplots (bivariate data) o Stem and leaf displays o Box plots o Other suitable charts For non-graphical techniques consider using techniques such as o Assessing central tendencies such as mean, median and mode (univariate) o Assessing variability such as range, interquartile range (IQR), variance, standard deviation Please note that you should discuss the interpret the results. Deliverables Prepare a report that includes the following: A clear, concise, and coherent description/summary of the dataset (200-300 words) Discussion on the data wrangling techniques you have used and the rationale behind using them (200-300 words) A clear, concise, and coherent summary of the EDA techniques used, analysis of results, and your finding including one or more low-level questions in 600-700 words. You may have applied various EDA techniques; however, you should mainly focus on those which have enabled you to craft relevant and valuable questions about the business case. Attach insightful graphs, tables etc. that you have developed to support your discussion. Expected total report word count: 1100-1300 words.