to what extent does brand recognition influence individuals’ ability to accurately identify the brand of a cookie and how does this affect their flavor perception, and how can mathematical models help explain these phenomena?”

!!!!!THIS IS AN 9 PAGE PAPER!!!!!!!

REQUIRES EQUATIONS

I collected data from 25 people asking them if they could tell the difference between namedbrands including oreos, chips ahoy, and cheez its. Then I gave them the off-brands which included Twisters (Offbrand oreos), Chips Galore (offbrand chips ahoy), and CHZ^2 (offbrand cheez-its). 17/25 guessed incorrectly for the oreos, 19/25 guessed incorrectly for the chips ahoy, and 9/25 guessed incorrectly for the cheez-its. I asked questions how it tastes, whihc one they like better, how they feel. Every time each individual automatically assumed the better tasting cookie was the name brand. This brings forth the question, what is the purpose of paying more for the name brand if it does not taste as good as the offbrand, are people paying simply for the name, or are people easily influenced etc. Using this data, adequately answer the prompt. Create equations and mathematical models to answer, converting qualitative data to quantitative. This paper is 11 pages, including data, equations, graphs etc with written analysis and explantions. Here is how to format: 

Introduction: 

1. Can the topic be clearly identified? 

2. How did you collect your data? What questions did you ask? Did you do a survey? Who answered it? Did you give it personally or over social media?

3. Do you have well defined processes and well defined parameters?

1. Step by step explanations.

2. What are your variables?

3. What do you need to find to complete your process?

4. What else do you need to know?

4. All processes should be in the order that you will complete them. Correlation must be completed before Linear Regression, so it should be described in the introduction before linear regression. (Not always applicable)

   5. Make sure your pages are numbered and that your work is double spaced. 

   
   

   Data: 

   1. Data collected through observation (stated above) and research

   2.  Data should be relevant

   3.  Data should be organized in a form that is appropriate for analysis

   4. Data taken from another source must be cited and must be raw, unanalyzed data; do not use percentages for Chi Squared

   
   

   1. Data analysis: 

      1. If creating a graph, make sure everything is labeled
      2.  Show ALL work, every step
      3. Include all equations
      4. After each process, give a brief explanation to the results of the process and how they connect to your topic
      5. Create your model, then use technology to compare
      6. Analyze for extrapolating and interpolating data

      
      

      conclusion:
      1. Create a meaningful conclusion, bringing back together all of your processes and summarizing the results
      2. Explain how each process connects to bring you to the conclusion of either proving or disproving your hypothesis
      3. Indicate validity – did the processes you used properly help you get to the conclusion you wanted to achieve? Is there any other process that could have been added or anything you would have done differently?
      4. Discuss reliability of your model if using statistics
      5. Think of real world applications, do outside factors affect the outcome?
      6. Could this project lead you into more research or analysis? How?
      7. BE REFLECTIVE!