Order ID 53563633773 Type Essay Writer Level Masters Style APA Sources/References 4 Perfect Number of Pages to Order 5-10 Pages Description/Paper Instructions
Topic: Data Analytics Project
Paper details:Purpose – 1) Perform in-depth data analytics on a dataset to learn about the analysis of data and to create a report that clearly articulates the patterns and insights you found from your data analytics work; 2) Learn the basics of webpage design; 3) Learn about data analytics from other students in the class.
Step 1: Plan for your Data Analytics Project (5 points):
You will need to create a plan for your analytics project. This plan should be no more than one page long. You will need to address three things in the plan:
1) Name and Source of the Dataset you will use for your project. (Example: Immigration 2015-2018 Dataset from kaggle.com). The most popular place for students to find a dataset is https://www.kaggle.com/datasets but it is fine for you to use a dataset from another source. Since there are a lot of datasets on kaggle.com, pick one that you think would be interesting to analyze. Download the dataset to your computer so you’ll have it available when you start on Step 2 of the project and make sure you can open it in Excel. IMPORTANT NOTE: No more than 2 students may cover the same dataset. If more than two students select the same dataset, I will approve the two students with the best plan and the other students will need to choose a different dataset.
2) You will need to create 7 questions. For each of the 7 questions, state the following: 1) The question you are going to explore in your analysis; 2) State how you will analyze the data to answer the question; 3) State whether it is a simple or complex analysis.
For you to get an A on your Step 2 project grade (the major part of the project grade), you will need to have at least two questions requiring a complex analysis. To be considered a complex analysis, you will need to use Excel tools such as correlation, pivot tables, ANOVA, and regression to analyze the data (there are plenty of online videos and websites describing how to do these analyses). If you are only answering questions using a simple analysis, such as answering the questions with sums and totals, then state that it is a simple analysis. There’s no need to do a complex analysis for all of your questions, but a student who performs a more complex analysis to answer 2-3 of the questions will get more points on Step 2 of the project than a student who only has a simple analysis to answer questions.
As an example, below are questions that a student may write up if examining a dataset on NBA Player salaries:
a. What has the percent growth been in NBA salaries each year? – I will sum the totals of each year’s salaries and then calculate percent growth per year to answer this. (SIMPLE)
b. Which are the teams that had the highest salaries? – I will sum the total salaries per team and then find the top 5 teams that pay the most in salaries. (SIMPLE)
c. Does the amount of salaries affect the amount a wins that a team has? – I will see if there is a statistically significant correlation between the total salary that a team pays and the amount of wins the team has. (COMPLEX)
d. Does the player salary correlate with a higher percentage of shots made? – I will see if there is a statistically significant correlation between the salaries of players and their percentage of shots made. (COMPLEX)
On some of the datasets, kaggle.com has descriptions about the data in the dataset and some questions that could be explored. If the dataset you are using has some questions, you can either choose to explore questions that kaggle.com has listed or you can create your own questions. Note that it is important to come up with questions that you will be able to answer by analyzing the data. Don’t create a question that you won’t be able to answer from your dataset. You will need to include an Excel graphical chart as a part of each of your answers, so they will need to be questions that are comparing data, looking at trends, etc.
Purpose – 1) Perform in-depth data analytics on a dataset to learn about the analysis of data and to create a report that clearly articulates the patterns and insights you found from your data analytics work; 2) Learn the basics of webpage design; 3) Learn about data analytics from other students in the class.Step 1: Plan for your Data Analytics Project (5 points):
You will need to create a plan for your analytics project. This plan should be no more than one page long. You will need to address three things in the plan:
1) Name and Source of the Dataset you will use for your project. (Example: Immigration 2015-2018 Dataset from kaggle.com). The most popular place for students to find a dataset is https://www.kaggle.com/datasets but it is fine for you to use a dataset from another source. Since there are a lot of datasets on kaggle.com, pick one that you think would be interesting to analyze. Download the dataset to your computer so you’ll have it available when you start on Step 2 of the project and make sure you can open it in Excel. IMPORTANT NOTE: No more than 2 students may cover the same dataset. If more than two students select the same dataset, I will approve the two students with the best plan and the other students will need to choose a different dataset.
2) You will need to create 7 questions. For each of the 7 questions, state the following: 1) The question you are going to explore in your analysis; 2) State how you will analyze the data to answer the question; 3) State whether it is a simple or complex analysis.
For you to get an A on your Step 2 project grade (the major part of the project grade), you will need to have at least two questions requiring a complex analysis. To be considered a complex analysis, you will need to use Excel tools such as correlation, pivot tables, ANOVA, and regression to analyze the data (there are plenty of online videos and websites describing how to do these analyses). If you are only answering questions using a simple analysis, such as answering the questions with sums and totals, then state that it is a simple analysis. There’s no need to do a complex analysis for all of your questions, but a student who performs a more complex analysis to answer 2-3 of the questions will get more points on Step 2 of the project than a student who only has a simple analysis to answer questions.
As an example, below are questions that a student may write up if examining a dataset on NBA Player salaries:
a. What has the percent growth been in NBA salaries each year? – I will sum the totals of each year’s salaries and then calculate percent growth per year to answer this. (SIMPLE)
b. Which are the teams that had the highest salaries? – I will sum the total salaries per team and then find the top 5 teams that pay the most in salaries. (SIMPLE)
c. Does the amount of salaries affect the amount a wins that a team has? – I will see if there is a statistically significant correlation between the total salary that a team pays and the amount of wins the team has. (COMPLEX)
d. Does the player salary correlate with a higher percentage of shots made? – I will see if there is a statistically significant correlation between the salaries of players and their percentage of shots made. (COMPLEX)
On some of the datasets, kaggle.com has descriptions about the data in the dataset and some questions that could be explored. If the dataset you are using has some questions, you can either choose to explore questions that kaggle.com has listed or you can create your own questions. Note that it is important to come up with questions that you will be able to answer by analyzing the data. Don’t create a question that you won’t be able to answer from your dataset. You will need to include an Excel graphical chart as a part of each of your answers, so they will need to be questions that are comparing data, looking at trends, etc.
3) Purpose – 1) Perform in-depth data analytics on a dataset to learn about the analysis of data and to create a report that clearly articulates the patterns and insights you found from your data analytics work; 2) Learn the basics of webpage design; 3) Learn about data analytics from other students in the class.Step 1: Plan for your Data Analytics Project (5 points):
You will need to create a plan for your analytics project. This plan should be no more than one page long. You will need to address three things in the plan:
1) Name and Source of the Dataset you will use for your project. (Example: Immigration 2015-2018 Dataset from kaggle.com). The most popular place for students to find a dataset is https://www.kaggle.com/datasets but it is fine for you to use a dataset from another source. Since there are a lot of datasets on kaggle.com, pick one that you think would be interesting to analyze. Download the dataset to your computer so you’ll have it available when you start on Step 2 of the project and make sure you can open it in Excel. IMPORTANT NOTE: No more than 2 students may cover the same dataset. If more than two students select the same dataset, I will approve the two students with the best plan and the other students will need to choose a different dataset.
2) You will need to create 7 questions. For each of the 7 questions, state the following: 1) The question you are going to explore in your analysis; 2) State how you will analyze the data to answer the question; 3) State whether it is a simple or complex analysis.
For you to get an A on your Step 2 project grade (the major part of the project grade), you will need to have at least two questions requiring a complex analysis. To be considered a complex analysis, you will need to use Excel tools such as correlation, pivot tables, ANOVA, and regression to analyze the data (there are plenty of online videos and websites describing how to do these analyses). If you are only answering questions using a simple analysis, such as answering the questions with sums and totals, then state that it is a simple analysis. There’s no need to do a complex analysis for all of your questions, but a student who performs a more complex analysis to answer 2-3 of the questions will get more points on Step 2 of the project than a student who only has a simple analysis to answer questions.
As an example, below are questions that a student may write up if examining a dataset on NBA Player salaries:
a. What has the percent growth been in NBA salaries each year? – I will sum the totals of each year’s salaries and then calculate percent growth per year to answer this. (SIMPLE)
b. Which are the teams that had the highest salaries? – I will sum the total salaries per team and then find the top 5 teams that pay the most in salaries. (SIMPLE)
c. Does the amount of salaries affect the amount a wins that a team has? – I will see if there is a statistically significant correlation between the total salary that a team pays and the amount of wins the team has. (COMPLEX)
d. Does the player salary correlate with a higher percentage of shots made? – I will see if there is a statistically significant correlation between the salaries of players and their percentage of shots made. (COMPLEX)
On some of the datasets, kaggle.com has descriptions about the data in the dataset and some questions that could be explored. If the dataset you are using has some questions, you can either choose to explore questions that kaggle.com has listed or you can create your own questions. Note that it is important to come up with questions that you will be able to answer by analyzing the data. Don’t create a question that you won’t be able to answer from your dataset. You will need to include an Excel graphical chart as a part of each of your answers, so they will need to be questions that are comparing data, looking at trends, etc.
3) Analysis of Data – State each of the 7 questions you are answering and then your answer to each question. Type your answer to your question and use a graphical chart to support every answer. For example, to answer the percent growth in NBA salaries each year, I could state the answer and then include an Excel bar chart to support the answer. To answer the question about the teams that had the highest salaries, I could list the teams that had the highest level and then include an Excel bar chart. Also, as stated in Step 1 of the project, remember that the complexity of your analysis will affect your grade and that you will need to have at least two complex analyses in order to get an A.4) Conclusion – should have 4-6 paragraphs addressing the following questions
a. What have you learned from the data analysis?
b. How could a manager of an organization use your analysis to improve their organization?
c. What additional data would have been useful in the dataset? (For example, for the NBA salaries dataset, if more data was provided in the dataset on each player’s performance, then more useful reports could be generated to determine the performance of each player and his value to the team based on his salary)
RUBRIC
QUALITY OF RESPONSE NO RESPONSE POOR / UNSATISFACTORY SATISFACTORY GOOD EXCELLENT Content (worth a maximum of 50% of the total points) Zero points: Student failed to submit the final paper. 20 points out of 50: The essay illustrates poor understanding of the relevant material by failing to address or incorrectly addressing the relevant content; failing to identify or inaccurately explaining/defining key concepts/ideas; ignoring or incorrectly explaining key points/claims and the reasoning behind them; and/or incorrectly or inappropriately using terminology; and elements of the response are lacking. 30 points out of 50: The essay illustrates a rudimentary understanding of the relevant material by mentioning but not full explaining the relevant content; identifying some of the key concepts/ideas though failing to fully or accurately explain many of them; using terminology, though sometimes inaccurately or inappropriately; and/or incorporating some key claims/points but failing to explain the reasoning behind them or doing so inaccurately. Elements of the required response may also be lacking. 40 points out of 50: The essay illustrates solid understanding of the relevant material by correctly addressing most of the relevant content; identifying and explaining most of the key concepts/ideas; using correct terminology; explaining the reasoning behind most of the key points/claims; and/or where necessary or useful, substantiating some points with accurate examples. The answer is complete. 50 points: The essay illustrates exemplary understanding of the relevant material by thoroughly and correctly addressing the relevant content; identifying and explaining all of the key concepts/ideas; using correct terminology explaining the reasoning behind key points/claims and substantiating, as necessary/useful, points with several accurate and illuminating examples. No aspects of the required answer are missing. Use of Sources (worth a maximum of 20% of the total points). Zero points: Student failed to include citations and/or references. Or the student failed to submit a final paper. 5 out 20 points: Sources are seldom cited to support statements and/or format of citations are not recognizable as APA 6th Edition format. There are major errors in the formation of the references and citations. And/or there is a major reliance on highly questionable. The Student fails to provide an adequate synthesis of research collected for the paper. 10 out 20 points: References to scholarly sources are occasionally given; many statements seem unsubstantiated. Frequent errors in APA 6th Edition format, leaving the reader confused about the source of the information. There are significant errors of the formation in the references and citations. And/or there is a significant use of highly questionable sources. 15 out 20 points: Credible Scholarly sources are used effectively support claims and are, for the most part, clear and fairly represented. APA 6th Edition is used with only a few minor errors. There are minor errors in reference and/or citations. And/or there is some use of questionable sources. 20 points: Credible scholarly sources are used to give compelling evidence to support claims and are clearly and fairly represented. APA 6th Edition format is used accurately and consistently. The student uses above the maximum required references in the development of the assignment. Grammar (worth maximum of 20% of total points) Zero points: Student failed to submit the final paper. 5 points out of 20: The paper does not communicate ideas/points clearly due to inappropriate use of terminology and vague language; thoughts and sentences are disjointed or incomprehensible; organization lacking; and/or numerous grammatical, spelling/punctuation errors 10 points out 20: The paper is often unclear and difficult to follow due to some inappropriate terminology and/or vague language; ideas may be fragmented, wandering and/or repetitive; poor organization; and/or some grammatical, spelling, punctuation errors 15 points out of 20: The paper is mostly clear as a result of appropriate use of terminology and minimal vagueness; no tangents and no repetition; fairly good organization; almost perfect grammar, spelling, punctuation, and word usage. 20 points: The paper is clear, concise, and a pleasure to read as a result of appropriate and precise use of terminology; total coherence of thoughts and presentation and logical organization; and the essay is error free. Structure of the Paper (worth 10% of total points) Zero points: Student failed to submit the final paper. 3 points out of 10: Student needs to develop better formatting skills. The paper omits significant structural elements required for and APA 6th edition paper. Formatting of the paper has major flaws. The paper does not conform to APA 6th edition requirements whatsoever. 5 points out of 10: Appearance of final paper demonstrates the student’s limited ability to format the paper. There are significant errors in formatting and/or the total omission of major components of an APA 6th edition paper. They can include the omission of the cover page, abstract, and page numbers. Additionally the page has major formatting issues with spacing or paragraph formation. Font size might not conform to size requirements. The student also significantly writes too large or too short of and paper 7 points out of 10: Research paper presents an above-average use of formatting skills. The paper has slight errors within the paper. This can include small errors or omissions with the cover page, abstract, page number, and headers. There could be also slight formatting issues with the document spacing or the font Additionally the paper might slightly exceed or undershoot the specific number of required written pages for the assignment. 10 points: Student provides a high-caliber, formatted paper. This includes an APA 6th edition cover page, abstract, page number, headers and is double spaced in 12’ Times Roman Font. Additionally, the paper conforms to the specific number of required written pages and neither goes over or under the specified length of the paper. GET THIS PROJECT NOW BY CLICKING ON THIS LINK TO PLACE THE ORDER
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