During this data analytics project, I had an idea of the common habits due to being a college student. I was intrigued on how these habits can influence GPA, such as the importance of calorie intake, eating healthy, taking vitamins, and playing sports can be. I wanted to grasp more by understanding college students eating lifestyle such as eating at home or at a fast-food restaurant. I was quick to notice that male college students prefer eating out and cooking less in comparison to females who cook more at home and eat out less. I concluded with how females statically had the higher GPA as oppose to male college students.
Throughout the journey of this project, I was able to understand college students eating habits but more importantly how to structure data to charts, graphs, and use functions through Microsoft Excel and Word. Many of these functions consisted of: countifs, averegeifs, vlookup, maximum, and minimum. I was able to excel my undergraduate studies and develop valuable experience, knowledge, and skills that will prepare me for my future for information systems. In addition, this analytic project enhanced my proficiencies in building a functional website to expand my creativity and designing traits.
The information from this database can be beneficial to managers of diet nutritional businesses. Also to college advisors and counselors, many college students struggle with being knowledgeable when it comes to nutritional diet. College students who move away for college are the ones who struggle the most with this, this is because they are moving away from home and they were mostly dependent on their parents to cook for them and when they are on their own they are lost tryin to find a needle in a haystack. Having this database allows managers to understand the habits of college students to assist with decision making and customer relation management.
Many college students do not know how food in their body not only can affect their health but also their academics. For example, if a student wakes up grabs a soda and a donut running out the door for class they might not do as well nor have the same energy level compared to college students who make the extra effort to have a nutritional and low calorie breakfast. By giving your body the right amount of energy and calories, this stimulates the brain and can increase college students GPA's.
Additional data that would have been useful to make more connections between GPA’s and nutrition, would’ve been the number of college students who eat breakfast versus the ones who do not. Thus, it is the most important meal of the day and fuels your body for the rest of the day. In the dataset it did show which college students make healthier choices for breakfast compared to the rest, but nowhere did it mention the number of college students who didn’t eat at all. Having the data of the college students who don't eat breakfast at all would have taught me if not eating at all is a detriment to health and GPA. It would have been beneficial to acquire the number of students who moved away for college versus the ones who stayed living at home. As I mentioned in the previous paragraph, college students living on their own can really affect individual eating habits such as not knowing how to cook healthy meals. Another helpful dataset that could’ve been an asset to my project would have been to have an even number of males and females to have a precise average for correlating differences between the two. Even though the difference in gender was slightly different, this still allowed me to understand what each gender favored. Lastly, the number of full-time college students who also work full-time would’ve been useful, due to the fact that balancing work and school can be challenging especially if you are full time in both.
Throughout the journey of this project, I was able to understand college students eating habits but more importantly how to structure data to charts, graphs, and use functions through Microsoft Excel and Word. Many of these functions consisted of: countifs, averegeifs, vlookup, maximum, and minimum. I was able to excel my undergraduate studies and develop valuable experience, knowledge, and skills that will prepare me for my future for information systems. In addition, this analytic project enhanced my proficiencies in building a functional website to expand my creativity and designing traits.
The information from this database can be beneficial to managers of diet nutritional businesses. Also to college advisors and counselors, many college students struggle with being knowledgeable when it comes to nutritional diet. College students who move away for college are the ones who struggle the most with this, this is because they are moving away from home and they were mostly dependent on their parents to cook for them and when they are on their own they are lost tryin to find a needle in a haystack. Having this database allows managers to understand the habits of college students to assist with decision making and customer relation management.
Many college students do not know how food in their body not only can affect their health but also their academics. For example, if a student wakes up grabs a soda and a donut running out the door for class they might not do as well nor have the same energy level compared to college students who make the extra effort to have a nutritional and low calorie breakfast. By giving your body the right amount of energy and calories, this stimulates the brain and can increase college students GPA's.
Additional data that would have been useful to make more connections between GPA’s and nutrition, would’ve been the number of college students who eat breakfast versus the ones who do not. Thus, it is the most important meal of the day and fuels your body for the rest of the day. In the dataset it did show which college students make healthier choices for breakfast compared to the rest, but nowhere did it mention the number of college students who didn’t eat at all. Having the data of the college students who don't eat breakfast at all would have taught me if not eating at all is a detriment to health and GPA. It would have been beneficial to acquire the number of students who moved away for college versus the ones who stayed living at home. As I mentioned in the previous paragraph, college students living on their own can really affect individual eating habits such as not knowing how to cook healthy meals. Another helpful dataset that could’ve been an asset to my project would have been to have an even number of males and females to have a precise average for correlating differences between the two. Even though the difference in gender was slightly different, this still allowed me to understand what each gender favored. Lastly, the number of full-time college students who also work full-time would’ve been useful, due to the fact that balancing work and school can be challenging especially if you are full time in both.