Title what food group has the most effect of the CO2 emissions
Title what food group has the most effect of the CO2 emissions
Hypothesis-
Result is r squared number
Protein= 0.4007 biggest relationship with the co2 emmisons
Fat= 0.0000- no relationship
Salt= 0.0106
Sugar = 0.0172
The hypothesis could be structured around comparing the coefficients of determination (R-squared values) of different food groups in their relationship with CO2 emissions. Here's a possible hypothesis:
"Based on the R-squared values obtained from the analysis, the food group with the highest R-squared value, specifically protein (R-squared = 0.4007), exhibits a stronger and more substantial relationship with CO2 emissions compared to other food groups tested, namely sugar (R-squared = 0.0172), salt (R-squared = 0.0106), and fat (R-squared = 0.0000)."
This hypothesis suggests that protein content in food has a stronger association with CO2 emissions compared to sugar, salt, and fat content based on the R-squared values obtained from the analysis.
The hypothesis aims to investigate and determine which food group, among sugar, salt, protein, and fat, exerts the most pronounced influence on CO2 emissions associated with food production. It is hypothesized that the food group with the highest R-squared value in the regression analysis, signifying the greatest explanatory power in relation to CO2 emissions, will be indicative of the food group that contributes the most to the overall environmental impact associated with food production."
High protein- high co2
Protein independent
WHAT ARE DATA STUDY GROUPS?
Intensive 'collaborative hackathons', which bring together people with different skills to contribute towards solving a problem. Normally, in Study Group organisations someone acts as a 'Challenge Owner', providing real-world problems and data sets to be tackled by small groups (3-4 people) of researchers; researchers brainstorm and engineer data science solutions, presenting their work at the end of a given time window (usually a few days). In your case, you will have 4 weeks to submit the report once the study group ends.
In our study group, I am your challenge owner, and you have 2 hours to study your data, with the support of experienced researchers. Your team will work collaboratively to solve a realistic problem using appropriate data. Your aim is not to find a solution to such a big problem, but to point towards one of many possible solutions that is, you identify what the best course of action could/should be, just like a small piece of a large jigsaw puzzle.
The aim of this assignment from my perspective is for you, as Researchers, to have an opportunity to put knowledge into practice and go beyond individual interests to contribute to solving real world problems.
APPROACH
Dates: The Data Study Group will take place on 15/12/2023 1-3pm. On this day, you will get into teams and work on the challenges below. You will submit the report by 12/01/2024, 2pm.
On 15/12/2003, you should attend in person. If you are unable to attend in person, you will be expected to attend virtually on that day notify the lecturer, and a Zoom link will be provided. Should you be unable to attend on the day at all, you will be certainly allowed to submit your individual report, but it may be not possible to provide you with a team.
DURING THE STUDY GROUP YOU AND YOUR GROUP SHOULD:
Define the research question given the data you have available.
Define the analysis plan.
Allocate work within the group, e.g., define who is going to do which analysis.
Define the broad structure of the report.
THE ASSIGNMENT
A 1,250-word report synthetising your work (as usual, a 10% excess is tolerated, which would increase the limit to 1,375 words; please note you cannot add a further 10% to this limit). This is a collective effort, and you are encouraged to work together with your team even after the Data Study Group to obtain your final results if you need.
However: please note that this is an individual report, and you should be the sole author of the report you submit. The use of identical results to teammates is acceptable, and will not constitute plagiarism; shared text will be instead considered plagiarism.
ASSESSMENT
The text of the report will be marked individually, as the report has to be written individually. While I will mark assignments one-by-one, all within a team will have the same results, and a wrong analysis will affect all those in the same group. Statistical methods will be assessed in terms of the answer to these questions:
Is this test appropriate for what the researcher is trying to do? and
If appropriate, has the test been executed correctly?
For guidance on the content of the report, check the sample reports on Canvas.
CHALLENGES
These challenges are based on actual data, from various sources.
NOTE: challenges are generic on purpose, to give you the freedom to analyse one specific relationship. For instance, on a challenge exploring the impact of takeaways on food intake, you could explore the role of prices, promotions, personal characteristics (e.g., BMI, education), and so on, or a subgroup of related variables (e.g., prices and discounts; BMI and health). You and your group should choose the element to study based on personal interests within the group (primarily) and the results of the analyses you undertake (to a lesser extent).
In your report, you are expected to use the techniques we used in all the labs, as appropriate; for regressions, it is sufficient to run either a linear or a binary (logit) model, although you are encouraged to do both if it helps your team explain the data.
IMPORTANT NOTICE: Once you choose a challenge, you are not expected to use the entire dataset for that challenge if you do not need it. If your research question requires a focus on a smaller portion of the dataset, feel free to restrict the analysis to a subsample and make sure you explain the reasons in your report.
Similarly, you are not expected use all the variables in the dataset, only focus on those that are important, based on your research question/s as well as the existing literature on the topic.
FOOD TRADE
Overarching research question: Understanding the impact of trade on health and environment.
Dataset: trade_data.xlsx
This is from the Eurostat database.
Description of the challenge: Food trade is an important part of the UK economy, but also accounts for the import of a significant proportion of CO2 associated to food production abroad. In this challenge, the aim is to analyse trade data to determine the most appropriate options to reduce the environmental impact of trade.
CARBON FOOTPRINT OF FOOD SHOPPING
Overarching research question: Understanding the carbon footprint of food expenditures
Dataset: Supermarket shopping.xlsx
This is from previous research of Dr Luca Panzone.
Description of the challenge: Food production and consumption is an important contributor of greenhouse gas emissions in the UK. The aim of the study group is to analyse data on food sales, to determine how consumers can be motivated to reduce their carbon footprint.
VITAMIN D
Challenge: How can we improve the levels of vitamin D in the blood of the consumer?
Dataset: NDNS_data.xls
This is from the National Diet and Nutrition Survey.
Description of the challenge: Vitamin D consumption is important for a healthy life, and levels of vitamin D in the blood of UK citizens are generally low. The aim of this challenge is to understand what attributes are associated with blood-levels of vitamin D, to determine how to best address this problem.
POULTRY FARMING
Challenge: How can we develop poultry farming in a way that is acceptable to consumers?
Dataset: feedagene_data.xlsx
This is from previous research of Prof. Guy Garrod.
Description of the challenge: Poultry farming, like many other agriculture sectors, is changing rapidly, to improve its economic and environmental sustainability, for instance increasing automation in farms, or improving animal nutrition. Changes to current systems are going to be more successful if supported by consumers. The aim of this challenge is to identify consumer preferences for different technical and technological developments in poultry farming.
WASTE PRODUCTION
Challenge: How can we reduce non-recycled waste in the UK?
Dataset: waste_data.xlsx
This is data from DEFRA.
Description of the challenge: Households across Local authorities in the UK produce considerable amount of waste, which is either landfilled, incinerated, or recycled. Yet it is not known what drives waste production and recycling across local authorities. The aim of this challenge is to identify what drives waste production and recycling choices, to identify how policy can influence these decisions.
REPORT STRUCTURE
(The number of words in each section are indicative, feel free to use the limits you are comfortable with, as long as you respect the total word count)
Title Page (Compulsory, not in word count)
Add title, and a 150-word abstract that summarises problem, methods, and key results.
Indicate the full list of participants in your team in alphabetical order. This ensures that if Turnitin picks similarities between reports, I can quickly see that there is nothing wrong.
Short Literature review (~300 words)
Outline your interpretation of the Challenge. In this section, you need academic literature (plus other sources, if appropriate) to explain what is known about your research question, and why the broader literature thinks this is important. You do not need to make any reference to your data here, but what you present here should be linked to the data you have (that is, your dependent and independent variables).
Research questions (~50 words)
One sentence outlining what your one research question is, given what you wrote in the literature review.
Short Description of the data (~150 words)
Describe briefly what the data refers to. In this section, provide Summary statistics for the relevant variables (only refer to variables you use, please ignore the rest).
Results (~400 words)
Purely report the results, without commenting unless strictly necessary. For each item in the results section, indicate:
Method used.
The results you obtain and their interpretation.
Discussion and conclusions (~350 words)
Comment your results, aligning these comments with the literature review and the research question. Here, you need to discuss your findings in the context of the broader research literature, which you presented in your literature review above.
Note: Tables, figures (including captions and titles), and footnotes do not count towards the word count.
Bibliography (This is not in the word count)
Appendix (if needed it is not compulsory. This is not in the word count)
