[Solution]Reflect on your most recent visualisation project and try to sketch or write out the approach you took. What stages of activity did you undertake and in what sequence?

How satisfied are you with the results and what would you do differently if working on it again?

My most recent visualization project was a data analysis of an online survey that I conducted. The survey collected opinions from people in my local community on their views on police violence. In order to create this visualisation, I followed a series of steps:

Reflect on your most recent visualisation project and try to sketch or write out the approach you took. What stages of activity did you undertake and in what sequence?

1. Data Collection: First, I created the survey using a survey tool and distributed it across different social media platforms to reach out to participants in my local area. After collecting all responses, I then spent some time cleaning up the data by eliminating any irrelevant questions or answers so that only relevant pieces of information remained for further analysis and visualization.

2. Data Analysis: Once I had cleaned up the dataset, I used statistical techniques such as correlation matrices and simple linear regression models to get insights into how people’s opinions were related to one another. This helped me identify patterns in how participants answered the survey questions which can be seen in subsequent stages of activity.

3. Data Visualization: After analysing the data, I used software like Tableau and Microsoft Power BI to visualize my findings in clear graphs and charts which could be shared easily with other stakeholders or viewers who wanted to understand more about my research process without having to dive into complex datasets themselves. This also allowed me to tell stories through visuals – highlighting trends or correlations between different variables – which would otherwise remain undetected if viewed separately from one another..

4. Interpretation & Reflection: After creating these visuals, I took time to reflect on them critically – examining why certain patterns may exist and whether there are underlying causes behind them that need further investigation or explanation – before coming up with conclusions as well as potential areas for improvement when working on similar projects next time round.

Overall, although I am largely satisfied with this project’s final outcome after completing each step successfully (from data collection through interpretation & reflection), there is still more room for improvement when conducting similar projects going forward – particularly around ensuring accuracy at every stage of activity by double-checking all calculations made during both the analysis and visualisation phases; as well as finding ways of improving user experience when viewing visuals by making sure they are designed clearly enough so even non-data users can make sense of them easily!