In this assignment you will generate data visualizations from data sets provided below and formulate hypotheses based on the patterns you identify.
Part 1: Exploratory Data Analysis (approx. 400 words including captions)
(a) Brief introduction of the data you are presenting. Begin with a concise introduction to the dataset you are working with. Provide context about its source, relevance, and any key attributes. (More than one data set can be used; most importantly that the datasets are complementing each other and together supporting the hypothesis you will be developing)
(b) Create a minimum of two data visualizations that adhere to best practices for clarity and effectiveness. It is highly encouraged for high grades to also add a “ready made” third visual from Gap Minder or Our World in Data that would also support your hypothesis.
Ensure that your visualizations are well-labeled, appropriately scaled, and visually appealing.
Your visualizations should complement each other and should help you develop your hypothesis in part 2 of the assignment. Please ensure a strong connection between your visuals and the well thought hypothesis you will develop.
(c) Include figure captions. For each visualization, include descriptive figure captions. These captions should not only highlight essential elements within the figure but also provide a summary of the primary patterns or insights revealed by the visualization.
LO: #visualizations
Part 2: Hypothesis and Justification (approx. 200 words):
(a) Describe your hypothesis. Clearly articulate your hypothesis, which should be based on the patterns and insights derived from your data visualizations. Explain the research question or idea you aim to explore through your hypothesis.
(b) Explain how it builds on the data visualizations you present and any related readings.
Describe how your hypothesis is grounded in the data visualizations you presented in Part 1. Discuss any relevant readings or prior research that influenced the development of your hypothesis. This is highly encouraged and expected for high grades.
(c) Explain how your hypothesis can be tested. Provide specific predictions that can be measured using empirical evidence. Clarify the type of data or experiments required to support or refute your hypothesis.
(d) Explain how the hypothesis is plausible. Discuss why your hypothesis is plausible based on your understanding of the dataset, the context, and any prior knowledge. Highlight any logical reasoning or assumptions that support the validity of your hypothesis.
LO: #hypothesisdevelopment
Datasets:
-** Our World in Data: https://ourworldindata.org/**
Gapminder: Gapminder contains a wealth of data and visualization tools about important global trends. Some climate change related variables you can find in Gapminder include greenhouse emissions, material footprint, types of energy used, and sustainability from a large number of countries, In addition to examining how a variable changes over time for a given country, Gapminder allows for making comparisons among countries and investigating relationships between different variables. You can get information on the source of the data you use by clicking on the question mark next to the variable on the graph.
The World Bank provides free data for the public to use on a variety of topics. Search for climate change data and you can also navigate to specific countries.
Background reading (ONLY for students interested in climate change as a topic for Assignment 2):
*All topics of interest to students are welcome and students are not restricted to climate change as a topic.
NASA. (n.d.)._ What is climate change_? https://climate.nasa.gov/ Why/Use: On this website you can find information on the evidence, causes, effects, and solutions of climate change. This should illuminate some of the data that scientists collect used both to determine past climates and to predict changes.
Packages to create visualizations
You may use the software package of your choice. Some resources below:
CODAP, website link
Python, we suggest [matplotlib](https://www.google.com/url?q=https://matplotlib.org/&sa=D&ust=1507759643862000&usg=AFQjCNGd-OKZqpbZEaxzsNeL3rR1tlXURQ (or Seaborn: https://www.google.com/url?q=https://seaborn.pydata.org/&sa=D&ust=1507759643862000&usg=AFQjCNGTgedrzaNbqCcR9izvlQYq05Rzlw%29)
Excel: Microsoft Office Tutorials. (2015). Create a chart from start to finish. Retrieved July 11, 2015 from
Google sheets
IMPORTANT NOTES for students:
Appendix: You will need to create an Appendix (will not count towards your word) in the same document you will submit in which you take a screenshot of your raw data used for each of your figures. You can go something like Figure 1 Raw data, Figure 2 Raw data etc. For your “ready made” one no raw data are requested. Failure to submit the clear screenshots representative of your data WILL impact your grade.
**Be ready to discuss the details of your submission with your peers and instructor in the classroom
important notes from me :
the hypothesis should be concise, plausable, striaghtforward, falsefiable , testable example :Regular moderate exercise, defined as 30 minutes of brisk walking five times a week, increases average life expectancy by 5 years among non-smokers aged 50-60 year (example2) “Increasing the daily intake of vitamin C by 500mg will reduce the average duration of common cold symptoms from seven to five days among adults aged 20-40 years.”
the two visualisations must relate to each other and i prefer something about health and age expectancy for example (
Life expectancy at birth, total (years) – United Arab Emirates) and (
Prevalence of undernourishment (% of population) – United Arab Emirates) choose one country for the viuslazations which is uae ( united arab emirates) u will access to the visulazations data by (https://data.worldbank.org/ this link choose indicator then u will find the topics choose download the csv file then when u have both csvs open excel and copy the prefered country only which is uae for both and make a line chart make sure the visualisation provides a clear concise summary of the viusaliazation , clear labels that describes what each of the axis present-and include the units of the measurements
for the third visiualztion it will be ready from the same website u dont have to download csv file etc and it should support my hypothesis and relates to them
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