9:42 = QM ROBB: il antl 31%X DataAnal.. & BlTable of contentsIntroduction 3Problem background andobjectives 4Methodology and theory (743words)Mutual Information Score 5Z-score...

1 answer below »
No need to use python you can use Excel for this.










First find a data set. Then think about what predictive analysis you can do on it. Then select an analysis method that gives most relevant results in terms of predection



9:42 = QM ROBB: il antl 31% X DataAnal.. & Bl Table of contents Introduction 3 Problem background and objectives 4 Methodology and theory (743 words) Mutual Information Score 5 Z-score 5 Scatter plots, correlation, and linear regression Random Forrest Regressor Analysis Conclusion © © N oOo References 9:42 = QM ROBB: il antl 31% X DataAnal.. & Bl Table of contents Introduction 3 Problem background and objectives 4 Methodology and theory (743 words) Mutual Information Score 5 Z-score 5 Scatter plots, correlation, and linear regression Random Forrest Regressor Analysis Conclusion © © N oOo References MCO105 Data Analysis for Managers Task brief & rubrics Decision making under Uncertainty: the role of quantitative methods Students are required to prepare and submit a project* critically examining and evaluating key aspects of decision making under uncertainty. *Project: A written assessment assigned as part of independent learning and outside of class hours. Students are required to prepare and submit a project critically examining and evaluating key aspects of the assigned topic, that enables the development and application of entrepreneurial thinking and analytical skills necessary for project implementation. Propose a project that address to a problem related to real business or context. This is part of learning personalization, where students are recommended to focus on the application of quantitative methods in a field of their interest. This project intends to provide students with the capabilities of applying the concepts and techniques learned in the course within a business context. Each group of 4 or 5 students will define a topic or problem based on a real context, and preferentially use data and quantitative methods to evaluate the topic or problem. Finally, the group should make proposals to solve the chosen problem and recommend the most suitable course of action to take. Examples: • Barcelona city hall open data: http://opendata-ajuntament.barcelona.cat/en. Examples: evaluate operations in Bicing, evaluate the location of public facilities as schools, health center, social centers, transportation, etc. • Further Open Data webs: European Open Data: EU (https://www.europeandataportal.eu/en/homepage), Spain (https://www.ine.es/), Milano (http://dati.comune.milano.it/), New York (https://opendata.cityofnewyork.us/), etc. Outline: • Present a one-page proposal to be submitted on November 18th. Attention: Not submitting in time incur 3 points penalization. • The students are supposed to undertake a project based on a real-world problem, in which quantitative methods are suitable tools to propose solutions • It can be done based on either an actual company business or a proposed business plan model. • Real data should be considered if available. If it is not, a justification must be presented as well as how it was overcome. Likewise, data and its source must be shared. • Note that at least one quantitative method must be applied. • In case a piece of code or excel files are used, they should be sent separately during the submission. • Include an executive summary of at most one page. http://opendata-ajuntament.barcelona.cat/en https://www.ine.es/ Formalities • Group task – 4 to 5 students each group • Project to be upload in pdf • The list of references must be added in the end and cited next to the text when applied. • Wordcount: 2500-3000 words. • Cover, Table of Contents, References and Appendix are excluded of the total wordcount. • Font: Arial 12,5 pts. • Text alignment: Justified. • The in-text References and the Bibliography must be in Harvard’s citation style Submission: • Week (7) November 18th, 2022, 23:59 Barcelona time– Via Moodle (Turnitin). -> Present a one-page proposal to be submitted on. Attention: Not submitting incur 3 points penalization. • Week (10) Sunday December 11th, 2022, 23:59 Barcelona time– Via Moodle (Turnitin). -> Project Weight: This task is a 100% of your total grade for this subject. It assesses the following learning outcomes: • Outcome 1: Apply advanced quantitative business methodologies in business analytics frameworks • Outcome 2: Draw conclusions from data and make informed data analysis decisions • Outcome 3: Understand uncertainly in business environment Rubrics Learning Descriptors Fail Below 70% Fair 70-79 % Good 80-89% Exceptional 90-100% Purpose & Understanding KNOWLEDGE & UNDERSTANDING 10% Very poor coverage of central purpose, goals, research questions or arguments with little relevant information evident. Virtually no evidence of understanding or focus. Minimal understanding of purpose of the study; factual errors evident. Gaps in knowledge and superficial understanding. A few lines of relevant material. Reasonable understanding and clearly identifies the purpose, goals, research questions or argument. Reflect partial achievement of learning outcomes. A sound grasp of, and clearly identifies, the purpose, goals, research questions or argument. Some wider study beyond the classroom content shown. Effectively describes and explains the central purpose, arguments, research questions, or goals of the project; explanation is focused, detailed and compelling. Recognition of alternative forms of evidence beyond that supplied in the classroom. Content KNOWLEDGE & UNDERSTANDING 5% Content is unclear, inaccurate and/or incomplete. Brief and irrelevant. Descriptive. Only personal views offered. Unsubstantiated and does not support the purpose, argument or goals of the project. Reader gains no insight through the content of the project. Limited content that does not really support the purpose of the report. Very poor coverage. Displays only rudimentary knowledge of the content area. Reader gains few if any insights Presents some information that adequately supports the central purpose, arguments, goals, or research questions of the project. Although parts missing, it demonstrates a level of partially proficient knowledge of the content area. Reader gains some insights. Presents clear and appropriate information that adequately supports the central purpose, arguments, goals or research questions of the project. Demonstrates satisfactory knowledge of the content area. Reader gains proficient insights. Presents balanced, significant and valid information that clearly and convincingly supports the central purpose, arguments, research questions or goals of the project. Demonstrates in- depth and specialised knowledge of the content area. The reader gains important insights Organization COMMUNICATION 10% Information/content is not logically organized or presented. Topics/paragraphs are frequently disjointed and fail to make sense together. Reader cannot identify a line of reasoning and loses interest. Information/content is not, at times, logically organized or presented. Topics/paragraphs are frequently disjointed which makes the content hard to follow. The reader finds it hard to understand the flow of the report. Information/content is presented in a reasonable sequence. Topic/paragraph transition is unclear in places with linkages for the most part. Reader can generally understand and follow the line of reasoning, although work needed to be proficiently organized. Information/content is presented in a clear and understandable sequence. Topic/paragraph transition is good with clear linkages between sections and arguments. Reader can understand and follow the line of reasoning. Information/content is presented in a logical, interesting and effective sequence. Topics and arguments flow smoothly and coherently from one to another and are clearly linked. Reader can easily follow the line of reasoning and enjoyed reading the report. Style & Tone COMMUNICATION 5% Writing is poor, unclear and unengaging, and the reader finds it difficult to read and maintain interest. Tone is not professional or suitable for an academic research Writing is unengaging and reader finds it difficult to maintain interest. Tone is not consistently professional or suitable for an academic research project. Work Writing is usually engaging and keeps the reader’s attention. Tone is generally appropriate for an academic research project, although a clearer and more Writing style and tone is generally good and sustains interest throughout. Tone is professional and appropriate for an academic research project. Writing is compelling and sustains interest throughout. Tone is consistently professional and appropriate for an academic research project. project. A reorganization and rewrite is needed. needed on academic writing style. professional style and tone is needed. Use of References COMMUNICATION 5% Little or no evidence of reference sources in the report. Content not supported and based on unsubstantiated views. Most references are from sources that are not peer- reviewed or professional, and have uncertain reliability. Few if any appropriate citations are provided. Reader doubts the validity of much of the material. Professionally legitimate references are generally used. Fair citations are presented in most cases. Some of the information/content/evidence comes from sources that are reliable, but more academic sources needed to be convincing. Professionally and academically legitimate references are used. Clear and accurate citations are presented in most cases. The majority of the information/content/evidenc e comes from sources that are reliable. Presents compelling evidence from professionally and academically legitimate sources. Attribution is clear and accurate. References are 75% from primarily peer- reviewed professional journals or other approved sources. Formatting COMMUNICATION 5% Research project exhibits no formatting, or frequent and significant errors in Harvard formatting. There are too many errors in the Harvard formatting to be acceptable as a partially proficient piece. Harvard formatting is employed in the research project with minor errors. A review and rework of format and style of referencing in text and in the bibliography is needed. Harvard formatting is used accurately and consistently throughout the research project, although some issues are apparent as the reader is unable to find sources. Harvard formatting is used accurately and consistently throughout the research project. Accurate hyperlinks are included where required, making it easy for readers to review sources. Written Communication Skills COMMUNICATION 5% The written project exhibits multiple errors in grammar, sentence structure and/or spelling. Inadequate writing skills (e.g., weaknesses in language facility and mechanics) hinder readability and contribute to an ineffective research project. The written project exhibits errors in grammar, punctuation and spelling. The written project comes across as untidy and not properly checked for mistakes. Errors present in written communication make readability frustrating. Written research project displays good word choice, language conventions and mechanics with a few minor errors in spelling, grammar, sentence structure and/or punctuation. Errors do not represent a major distraction or obscure meaning. Readability of the project is good due to the clarity of language used. Grammar, spelling and punctuation is without error. Spelling and grammar thoroughly checked. Readability of the project is enhanced by facility in language use/word choice. Excellent mechanics and syntactic variety. Uses language conventions effectively (e.g., spelling, punctuation, sentence structure, paragraphing, grammar, etc.). Analytical / Critical Thinking Skills CRITICAL THINKING 30% Research problem, concept or idea is not clearly articulated, or its component elements are not identified or described. Research information is poorly organized, categorized and/or not examined; research information is often inaccurate or incomplete. Presents little if any analysis or interpretation; Research problem, concept or idea is not clearly articulated at times and confusing. Research information is badly organized, categorized, and/or only superficially examined; research information is often incomplete. Presents limited analysis or interpretation; inaccurately and/or Adequately identifies and describes (or sketches out) the research problem, concept or idea and its components. Gathers and examines information relating to the research problem, concept or idea; presents and appraises research information with some minor inconsistencies, irrelevancies or omissions. Formulates a clear description of the research problem, concept or idea, and specifies major elements to be examined. Selects information appropriate to addressing the research problem, concept or idea; accurately and appropriately analyses and
Answered 1 days AfterDec 09, 2022

Answer To: 9:42 = QM ROBB: il antl 31%X DataAnal.. & BlTable of contentsIntroduction 3Problem...

Rhea answered on Dec 10 2022
40 Votes
McDonalds Nutrition Value Analysis
Name
Subject
Professor’s Name
Year
Abstract
        The role of quantitative data analysis techniques in the decision making process of a business manager is pivotal. In this research, we propose to open a new fast food chain of healthier alternatives, “Fit-O-fish Joint”. As a starting point, to analyse the nutritional aspect of fast food in the current scenario, we have taken dataset of McDonald’s India menu. Various different items found in the outlets found in India have been tabulated and along with them the nutritional values of each food item on the menu has also been g
iven.
We shall observe how the calories contained in a food item related with its components namely carbohydrate, protein, fat, sodium etc. When we understand this relationship, we then make recommendations to increase/ decrease oil/sugar content in sauces, increase/decrease portions of meat, increase/decrease sugars in drinks, explore the option of low calorie natural sweeteners, etc.
Introduction
    Nutrition Analysis is used as a discipline which is dedicated to studying as well as characterising the economic and health effects of diet for the good of the society. This growing area of data analysis focuses on these interactions between food habits, health as well as public spending. It is the fusion of disciplines of nutrition as well as health as economics to find the impact nutrition has on health as well as disease, and to show the health and economic part of the daily diet changes and dietary suggestions through the lines of cost-effectiveness. It helps the development of nutrition, economics of health and evidence-based health-policy and health benefits. It will improve understanding of the effects of diet on health and its full and correlated monetary impact.
Nutrition Analysis
    Companies dealing with food send samples of foods to laboratories for analysis. Using various methods involving science, the sample of food so given is analysed in search of the various components that make up the necessary nutritional information of the food. The lab analysis will find the nutrient content in actuality in the given food, and will provide a high degree of accuracy as well as precision . Nutrition Analysis of the food sample takes into account changes in nutritional value caused by cooking as well as by the processing of food. This is extremely valuable as calories tend to increase or decrease during the cooking process which also depends on which method the process of cooking has been used. We can give the instance of adding oil increases the calorie count when frying and decreases the calorie-count when we are grilling. Also, salt which is used for seasoning during cooking, goes on to increase the sodium content of our food.
Description of the model
Regression equation:
    Y= Energy in calories
    X= Various components like carbohydrates, fat, protein and sodium
    Y= + X
Hypothesis:
    Null hypothesis: Components of food affects the level of calories
    Alternative hypothesis: Components of food does not affect the level of calories
Data description and model estimation
Data Description
Source of the Data
This research will incorporate data from the “McDonald’s India” official website which mandatorily provides nutritional data regarding its various items on its websites. Additionally, it also provides a list of allergens along with serving size and nutritional information. CPI measures the fluctuations in prices paid by consumers for goods and services. It is a key reflection of the changes in consumer spending during inflation.
https://www.mcdelivery.co.in/assets/pdf/McD_Allergen_and_Nutritional_Table.pdf
https://www.kaggle.com/datasets/deepcontractor/mcdonalds-india-menu-nutrition-facts?resource=download
Companies dealing with food send samples of foods to laboratories for analysis. Using various methods involving science, the sample of food so given is analysed in search of the various components that make up the necessary nutritional information of the food. The lab analysis will find the nutrient content in actuality in the given food, and will provide a high degree of accuracy as well as precision . Nutrition Analysis of the food sample takes into account changes in nutritional value caused by cooking as well as by the processing of food. This is extremely valuable as calories tend to increase or decrease during the cooking process which also depends on which method the process of cooking has been used. We can give the instance of adding oil increases the calorie count when frying and decreases the calorie-count when we are grilling. Also, salt which is used for seasoning during cooking, goes on to increase the sodium content of our food.
Figure-1 : Mc Donald’s India menu
We did some pre-processing on this dataset by removing some of the columns and keeping the more relevant ones. We removed the columns- Menu category, per serve size, Sat fat, trans fat, cholesterol, Total sugars and added sugars. We did this because we know that Cholesterol is resultant of total fat, carbohydrate is a resultant of the total sugars. At this point, we do not want to find how saturated and trans fat individually contribute to the total calories. The same is also true for total and added sugars. We also took the liberty of renaming some of the columns for easier coding. Hence, our dataset now looks somewhat like this-
Description of the Variables
    Variable
    Source
    Type
    Energy
    India_menu
    Dependent
    Protein
    India_menu
    Independent
    Fat
    India_menu
    Independent
    Carbohydrate
    India_menu
    Independent
    Sodium
    India_menu
    Independent
Figure-2
The explained variable to be tested is the Energy which is expressed in kcal or kilocalories (simply calories). The explanatory variables to be tested are the primary components of food, namely- Protein, Fat, Carbohydrate and Sodium. The first three i.e. Protein, Fat and Carbohydrate are given in grams (g) while sodium is given in milligrams (mg).
Scatterplots:
Energy v/s Protein
Figure-3
Energy v/s Fat
Figure-4
Energy v/s Carbohydrate
Figure-5
Energy v/s Sodium
Figure-6
Model...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here