generated from mwc/project_argument
9af355b539
After completing this project my recent success that I am proud of is that I was able to create visualizations with the data and topic I chose. This project has sparked the idea of how I could use this for sport statistics like one of my peers did. A new skill I learned doing this project was creating visualizations for the data I chose.
64 lines
3.3 KiB
Markdown
64 lines
3.3 KiB
Markdown
# Project proposal
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This planning document will also form the introduction of your
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argument.
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## Overarching Question
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How does time spent on social media affect happiness?
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### What central question are you interested in exploring? Why are you interested in exploring this question?
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The central question I am interested in is I’m interested in this question because social media is a major part of daily life, especially for young people. Some say it helps them connect with others, while others say it makes them feel less satisfied or distracted. I’m curious about this topic because I use social media every day and often wonder if the amount of time I spend online affects how happy I feel. I aim to investigate whether individuals who spend more time on social media report lower levels of happiness.
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### What specific research questions will you investigate?
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Do people who spend more time on social media report lower happiness?
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Is there a difference in happiness between people who use social media daily versus occasionally?
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Does age or gender affect how social media use relates to happiness?
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## Data source
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### What data set will you use to answer your overarching question?
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Dataset name: Mental Health & Social Media Balance Dataset
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Data source: Kaggle (public dataset)
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About the data: The dataset includes information on the number of hours people spend on social media each day, their reported happiness levels, and demographic details such as age and gender.
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### Where is this data from?
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The data will come from Kaggle, which is a trusted website where researchers and data scientists share datasets for learning and analysis. The specific dataset I plan to use was gathered from survey responses about social media use and happiness, collected by researchers studying the effects of screen time on well-being. I trust this data because Kaggle only allows verified datasets to be posted, and the information is based on real surveys where participants reported their habits and feelings.
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### What is this data about?
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The dataset contains survey results from people who were asked about their daily social media use and how happy they feel on a scale (for example, 1–10). It includes hundreds to thousands of rows, with each row representing one person’s response.
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Important columns include:
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Daily_Screen_Time(hrs) – number of hours per day on social media
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Happiness_Index(1-10) – how happy the person feels on a scale from 1 to 10
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Age – age of the respondent
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Gender – male, female, or other
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These columns will help me compare how time online relates to happiness and whether age or gender makes a difference.
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## Methods
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### How will you use your data set to answer your quantitative questions?
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To answer my research questions, I will use Python’s Pandas library to organize and analyze the data.
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For my first question, I will group the data by time spent online and calculate the average happiness score for each group. I’ll show this with a bar chart.
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For my second question, I will compare the mean happiness scores of these two groups in a table or bar graph.
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For my third question, I will create scatter plots or grouped bar charts to see if certain age groups or genders show stronger effects.
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I will use Seaborn to make clear, easy-to-read charts and provide a short written explanation for each result.
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