Aidan Diaz DSA-2 Deliverable

Aidan Diaz Revision and Log History Comment Action 9/28 - Started Revision Took first steps in completing DSA 1 9/29 - Personalized Grading Philosophy Watched DSA Template video and summarized Grading philosophy. 10/1 - Start Data Visualization Plan Began answering the first questions of this project. Did research about business analytics and combined that with what I already knew to come up with an answer. 10/2 – Finished Data Visualization Plan Answered question about the data gathering process after watching coaching video 1. 10/3 - Began Data Gathering Completed baseline survey and first daily survey. 10/5 - Started Approach and Methodology Wrote business question and explained why I chose it. Began working on visual for approach and methodology. 10/6 – Completed Approach and Methodology Completed visual and summary for each of the five steps of my approach and methodology. 10/10 – Began and Completed Timeline Began and completed writing out my plans for the rest of the semester to set myself up for success. 10/11 – Began Describing Dataset Went back through surveys and wrote out each question, answer choice, and why they pertained to this project. 10/12 – Completed Dataset Description Went back through surveys and wrote out each question, answer choice, and why they pertained to this project 10/16 – Completed Closing Survey Completed last daily survey and closing survey 10/16 - DSA submission Reviewed DSA 1 template thoroughly and submitted assignment DSA 2 Revision History 11/22 - Updated File Name Aidan Diaz DSA-2 Deliverable.docx 11/22 - Download Data Downloaded zip files and turned them into Excel .xlsx files 11/22 – Began adding to revision history Added green header and updated file name and data 11/27 – Altered and revised data on excel spreadsheets Deleted duplicates and simplified headers on Baseline, Daily and Closing spreadsheets 11/27 – Completed Section 3 Planned my data set and discussed plans for graphs in section 4 11/30 – Completed section 4 Finished making and adding graphs to document. Summarized each graph and explained reasoning for each one 11/30 – Completed Section 5 Made one visual with all four graphs on it and described each one Lance Kerwin – DSA Fall 2023 12/1/23 Page 1 of 17

Aidan Diaz Lance Kerwin – DSA Fall 2023 12/1/23 Page 2 of 17

Aidan Diaz DSA-1: Data Gathering Process 1. Data Visualization Plan What is Business Analytics? Business analytics is the process of solving business problems using data analysis and models. It allows firms to make informed decisions and strategically plan based on quantitative data. Business analytics helps with data management and visualization, making it easier for people to digest in a clear manner. It allows us to analyze current and historical data to gain new insight and improve on the past. It also allows us to predict things that could happen in the future based off current and historical data. With business analytics we can identify trends, patterns and root causes of things. It gives us strategic ways of looking at data to benefit a business. My concrete experience In high school I completed a science project in which I measured a population of plants that were exposed to different amounts of light and were given different amounts of water. In this project I used the scientific method to go about the data. I first asked the question, “what is more important to sustaining plant life; sunlight or water?”. I then researched the field and hypothesized that while both were extremely important, sunlight was more important for plant growth than water. I then tested this over a two weeklong period and analyzed my resulting data. I added different levels of water and exposed plants to different amounts of light over this two week period and recording the growth of each plant every day from Monday – Friday. I was able to conclude that both water and sunlight were very necessary for plant life and growth, however light had slightly more of an impact than water. This experience taught me a lot about how to follow the scientific method as well as analyzing data. Data Gathering Process The data gathering process starts on October 3 rd with the baseline survey. Each student will complete this baseline survey on October 3 rd . From October 3-16 th students will complete a daily survey that asks questions about their day. This survey will be completed each day (Saturday and Sunday is optional) for this period. On October 16 th students will complete a closing survey to wrap up the two previous weeks. The closing survey allows students to reflect on the two previous weeks. DSA-1 and DSA-2 Evaluation Process First and foremost, Lance and his team will assess the Data Science Activity by making sure that students watched the necessary videos to complete the assignment. Students must format the template according to these videos and add and delete anything Lance says in the videos. Students must name the file FirstName LastName DSA-1 Submission. Each student must include information about revision history to show how often they have been working on this assignment. Lance and his team have made it clear that only MS Doc or PDF files are acceptable and that there is zero tolerance for late work. The complete DSA project takes place form week 6 – 14 and is due on December 1 at 5pm. The goal for this project is to build a data story. When this assignment is being graded, students are competing against each other. Students can receive a grade below expectation, at expectations, or above expectations and each of these a different starting point for the grade. Both DSA 1 and DSA 2 are 150 points each. Technology issues are not a reason for not completing this assignment, work should be finished in advance of the due date and students should know the Canvas Help Desk hours in case anything does go wrong. Lance Kerwin – DSA Fall 2023 12/1/23 Page 4 of 17

Aidan Diaz Business Question What is the correlation between the amount of sleep students get on a given night versus their stress level the next day? I chose this question because sleep and stress are two very pertinent problems for college students, and they are closely related. This is a topic that affects me personally and I am curious and eager to find out more information on the subject. The data that I will look at when answering this question will be the question asking students how much sleep they got last night, as well as the question asking what their current stress level is. These questions will give sufficient first-hand insight into how sleep and stress are related. Lance Kerwin – DSA Fall 2023 12/1/23 Page 5 of 17

Aidan Diaz Timeline Week 6 Activities (Oct. 3-9):  Watch Tuesday morning lecture and take notes  Began data gathering for DSA 1  Began working on DSA 1 template Week 7 Activities (Oct. 10-16):  Watch Tuesday morning lecture and take notes  Finished DSA 1  Consume lecture materials and identify concepts that I can use in my DSA  Update Revision History, as necessary  Reviewed and Submitted DSA 1 Week 8 Activities (Oct. 17-23):  Watch Tuesday morning lecture and take notes  Begin studying for Exam 1  Begin working on DSA 2 Week 9 Activities (October 24-30)  Watch Tuesday morning lecture and take notes  Continue studying for Exam 1  Finish DSA 2 section 3 Week 10 Activities (October 31 - November 6):  Watch Tuesday morning lecture and take notes  Continue studying for Exam 1  Finish DSA 2 section 4 Week 11 Activities (November 7-13 th ):  Watch Tuesday morning lecture and take notes  Continue studying for Exam 1  Finish DSA 2 section 5 Week 12 Activities (November 14 – 20 th ):  Watch Tuesday morning lecture and take notes  Finish studying for Exam 1  Complete DSA 2 in its entirety Lance Kerwin – DSA Fall 2023 12/1/23 Page 7 of 17

Aidan Diaz Dataset Description Table 1: Baseline Survey (October 3) Attribute / Column Name Values Purpose for Collecting Data Identifier Student driven Students have the option to create an identifier that is either public, or private where they select a unique string of characters that only they will know the true identity. Performance Strategy Used Tracker; Used memory To see how students would rate their overall performance and growth Overall Approach Follow a structure program; follow my own; Didn’t follow To distinguish between those that used a structured program, those used their own program, to those that used limited structure Sleep Strategy Intentional and consistent sleep patterns OR No strategy, just sleep when I’m tired Analyze students approach to falling asleep on a given night Stress Level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 To see the stress levels of students at the time of the survey Emotion Emotions such as love, like, crying, laughing, angry, etc… To evaluate the emotions students were feeling at the time of the survey Time Preference Day or Night Allows students to be divided into two groups, those who prefer day and those who prefer night Pet Preference Cats, Dogs, Neither Allows students to be divided into two groups, those who prefer cats and those who prefer dogs and those who prefer neither Favorite Number Students type in their favorite number, personalized answer Puts each student into a category of what their favorite number is Heads or Tails Preference Heads or Tails Allows students to be divided into two groups, those who prefer heads and those who prefer tails Beach or Pool Preference Beach or Pool Allows students to be divided Lance Kerwin – DSA Fall 2023 12/1/23 Page 8 of 17

Aidan Diaz Table 3: Closeout Survey (October 16) Attribute / Column Name Values Purpose for Collecting Data Identifier Customizable Students have the option to create an identifier that is either public, or private where they select a unique string of characters that only they will know the true identity. Players Scored 1-5 1 was a goal, 5 is the worst score Sleep Strategy Intentional and consistent sleep patterns OR No strategy, just sleep when I’m tired Analyze students approach to falling asleep on a given night Stress Level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 To see the stress levels of students at the time of the survey Emoticon Like; Love; Caring; Crying; Laughing Face; Angry Face To evaluate the emotions students were feeling at the time of the survey Correlation between rest and performance Yes, No, Maybe To get students’ opinion on whether getting more rest can lead to a more productive day Growth in past 2 weeks Range 1-5, 1 being no growth and 5 being life changing growth To see how students felt they have grown and improved over the data gathering period of DSA 1 Time Preference Day or Night Allows students to be divided into two groups, those who prefer day and those who prefer night Pet Preference Cats, Dogs, Neither Allows students to be divided into two groups, those who prefer cats and those who prefer dogs and those who prefer neither Favorite Number Students type in their favorite number, personalized answer Puts each student into a category of what their favorite number is Heads or Tails Preference Heads or Tails Allows students to be divided into two groups, those who prefer heads and those who prefer tails Beach or Pool Preference Beach or Pool Allows students to be divided Lance Kerwin – DSA Fall 2023 12/1/23 Page 10 of 17

Aidan Diaz into two groups, those who prefer the beach and those who prefer the pool iPhone or Android Preference iPhone or Android Allows students to be divided into two groups, those who prefer iPhone and those who prefer Android Lance Kerwin – DSA Fall 2023 12/1/23 Page 11 of 17

Aidan Diaz 4. Storyboard In order to create my four graphs for this section of the DSA, I created several PivotTables and PivotCharts based on the data from my Excel spreadsheets. I wanted to see the relationship between how students value their sleep and their stress level. I wanted to make graphs that clearly showcase the correlation between the amount of sleep students get, how they approach their sleep schedule and their overall stress levels. I used different types of graphs including line graphs and bar charts and waterfall graphs to clearly show my data. Each different type of graph was used for a specific reason to tell a specific story about the data. Graph 1: Sleep Schedule vs Stress Level I would like to incorporate a two line slope graph because it clearly shows the two approaches for a sleep schedule that students were asked (orange and blue lines) as well as where their stress level was. This graph was interesting to me because students’ stress levels were extremely close regardless of their sleep strategy. This graph related to my business question because it shows a direct correlation between the amount of sleep students get and their stress level. Lance Kerwin – DSA Fall 2023 12/1/23 Page 13 of 17

Aidan Diaz Graph 2: Stress Level vs Emotion This graph shows the relationship between students’ stress levels and the emoticon that they picked to describe their emotion. Overall, most students picked the thumbs up emoticon which insinuates a low stress level, however many students with high stress levels picked this as well. In theory, the students with the highest stress levels would have picked an emoticon such as the angry face or crying sad face, however this was not necessarily the case. I chose to use a bar chart for this set of data because it clearly shows which emoticons were most frequently used based on what stress level the student was feeling. The legend on the right side of the graph makes this very easy to read quickly as well. This relates to my business question when compared to graph three to show if there was a correlation between sleep, stress, and the emotions students were feeling at the time of the survey. Lance Kerwin – DSA Fall 2023 12/1/23 Page 14 of 17

Aidan Diaz Graph 4: Hours of Sleep vs Stress Level This graph most closely relates to my business question, “What is the correlation between the amount of sleep students get on a given night versus their stress level the next day?”. I chose to use a waterfall bar chart for this set of data because it clearly shows how students’ stress levels compare to their average hours of sleep per night. It shows that most students had a stress level between six and eight and slept anywhere from three to seven hours per night. Lance Kerwin – DSA Fall 2023 12/1/23 Page 16 of 17

Aidan Diaz 5. Storytelling with Data The visual shown below shows all four of the graphs from section four put into one display. This visual shows data from the rest and performance daily survey as well as the closing survey. Each type of graph was specifically chosen for the type of data that was being shown. Sleep Schedule vs Stress Level: This graph shows the correlation between a students’ sleep schedule and their overall stress. It shows that regardless of their sleep schedule, their stress remains quite similar. Stress Level vs Emotion: This graph shows the correlation between students’ stress levels and the emoticon they chose to describe their emotion. The graph shows that the thumbs up emoticon was the number one choice by a landslide. Hours of Sleep vs Emotion: This graph shows the correlation between how much sleep students’ get on an average night and the emoticon they chose to describe their emotion. Like the last one, it shows that students chose the thumbs up emoticon the most regardless of how much sleep they got. Hours of Sleep vs Stress Level: This waterfall graph shows students’ stress levels for their average hours of sleep per night. This relates directly to my business question which asks about the correlation between students’ stress levels and the amount of sleep they get on a given night. Lance Kerwin – DSA Fall 2023 12/1/23 Page 17 of 17