ICT110 Introduction to Data Science Assignment Help and

Assignment Detail:- ICT110 Introduction to Data Science - University of the Sunshine Coast Assignment Part You work at Real Beer as a data scientist- The product development team have approached you because they want to develop a new line of beer- Real Beer has a long history in the brewery market, but their target market has typically been pitched at the lower end- They are now looking to develop a range of beer for very discerning beer connoisseurs- This beer will be more expensive and will be sold through specialty stores or direct sales on a new website- The product development team aren't sure what the characteristics of this new beer should have taste wise but know that they want it to have distinctive characteristics- An executive in the product development team at Real Beer head office has provided you with a dataset with most current producers and has asked you to provide a report with recommendations about what attributes this new beer could have- Note: not all columns are related to this purpose-You need to use the data to develop a cohesive and convincing story that describes the process of finding the key features of a top beer- First, the product development team would like to get a better understanding about what sorts of attributes top beers have- They have asked you to describe the data and find interesting phenomena- Second, the product development team have asked you to explore the data in more detail- They would like you to use your expertise in data science to dig out anything you feel is interesting or significant- They are looking for attributes of top beers that could be put together to create a distinctive yet tasty beer- You are required to prepare a report about your findings and to make suggestions about which attributes you would recommend be considered in the new product - whether it be based on some values, such as style, IBU, sweet, sour, etc- The potential audiences of this report include other staff within Real Beer, such as executives or sales staff - this means that each graph will need a detailed explanation and some narrative around why or how this image adds to the story- Staff may have limited ICT or mathematical knowledge therefore the report should be technical but have clear explanations describing the findings- To prepare the report, please include the following sections: 1- IntroductionProvide an introduction to the problem- Include background material as appropriate: who cares about this problem, what impact it has, where does the data come from, what are the dimensions and structure of the data- 2- Data SetupDescribe how to load the data, and how the pre-processing is performed- The original dataset is not ready for analysis and it is different from the data forms that we are familiar with in previous practices- This means we need to do some pre-processing, either for the whole dataset, or for a subset of the dataset required for each sub task described later- Once you have some ideas of exploratory or advanced analysis, you need to adjust the form of dataset- This can be achieved either by manipulating records in R by transposition or subsetting, or with other tools -e-g- notepad or excel- before reading them into R- Please clearly explain the way you have cleaned the data in this section- If you use Excel please still explain the steps that you used for cleaning- 3- Exploratory Data AnalysisTwo, one-variable analyses with graphs One-variable analysis studies one variable -one column/attribute- each time- You can choose the attribute you want to for this but the attributes you select need to add to the story you are telling about which features are keys to a top beer- • Perform 2 one-variable analyses and graph them• Explain the findings for each graph• Provide the code for each graph Two, two-variable analyses with graphs A two-variable analysis studies the relation between two variables- It is up to you to decide which attributes/variables you use for this analysis but the attributes you select need to add to the story you are telling about which features are keys to a top beer- • Perform 2 two-variable analyses and graph them• Explain the findings for each graph• Provide the code for each graph 4- Advanced Analysis Two, Linear regression analyses with graphs Briefly explain the concept of linear regression -with references-- It is up to you to decide which attribute/s you use for this analysis- You may choose to use any two attributes for this but the values you select need to add to the story you are telling about which features are keys to a top beer- • Perform 2 linear regression analyses and graph them• Explain the findings for each graph• Provide the code for each graph Decision treeBriefly explain the concept of decision trees -with references-- It is up to you to decide which attribute/s you use for this analysis- You may choose the attributes for this but the values you select need to add to the story you are telling about which features are keys to a top beer- • Create a decision tree and resulting visualisation• Explain the findings for the decision tree• Provide the code for the decision tree 5- ConclusionSum up your findings and provide some insight into the findings- Provide your overall recommendation/s in this section eg- which features have you selected and why- 6- ReflectionsIn this part, discuss any difficulties you had performing the analysis and how you solved those difficulties- Reflect on how the analysis process went for you, what you learnt, and what you might do differently next time- Aim to write 2-4 paragraphs- Report Format Your report should be no less than 1,200 words and it would be best to be no longer than~2,000 words long- Texts in R code snippets are not counted- The report MUST be formatted using the following guidelines: 1- Title Page - Include your name as the report's author- 2- Header - Report title 3- Footer - your name and the page number 4- Paragraph text - 12 point Calibri or Times New Roman single line spacing 5- Headings - In an appropriate type and size 6- Margins - 2-5cm on all margins 7- Page numbering - Introduction and onwards to use conventional numerals -1, 2, 3, 4- starting on page 1 from the introduction- Attachment:- Introduction to Data Science-rar




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