Using Math to Analyze and Present Real-World Data by Adam Torres

adamtorres4 — 2024-11-18 05:18:17 UTC

We surveyed 30 classmates to find the most popular snack choices. The Bar Graph displays the frequency of votes for each snack option. After reviewing our data, we found that chips were the most popular snack (40% of votes), and candy was the least popular. This surprised us because we expected candy to rank higher.

adamtorres4 — 2024-11-18 05:25:59 UTC

We analyzed scores from our school’s last 10 basketball games to determine average performance.

Data Analysis:

Mean (Average Score): 68
Median Score: 68.5
Range of Scores: 15

Scatter Plot: The graph above compares our team’s scores with the opponent’s scores for each game, highlighting performance trends and the average margin of victory.

The data showed consistent scoring patterns, with The data showed consistent scoring patterns, with an average margin of victory of 10 points. This analysis highlights the team's strong performance and potential areas for improvement against tougher opponents.

adamtorres4 — 2024-11-18 05:33:58 UTC

We examined how daily screen time correlates with grades in math.

Data Analysis:

Highest Performance: Students with 2-4 hours of screen time achieved the highest grades, with an average score of 88%.
Decline in Performance: Grades decreased steadily with screen time exceeding 4 hours per day.
Insights: Moderate screen time may allow students to balance academic focus with activities, while excessive screen time can hinder focus and productivity.

This data highlights the importance of balance in screen time for academic success. While minimal screen time correlates with lower grades, excessive use shows bad results. We concluded that 2-4 hours of screen time might provide the best balance for learning and activities. These insights could help guide students in managing their time effectively.

adamtorres4 — 2024-11-18 05:45:21 UTC

We recorded daily high temperatures in our city for one week to explore weather trends. We aimed to analyze how temperatures changed over time during this short period and identify any patterns.

Data Analysis:

Median Temperature: 65°F
Range: High of 68°F and low of 62°F (range of 6°F).
Interquartile Range (IQR): Highlights the middle 50% of the temperatures, showing a steady cooling trend.

Box Plot: The box plot visually summarizes the data, displaying the range, median, and variability of temperatures throughout the week. The box plot provided a clear summary of the weekly temperatures, showing a steady cooling trend. This analysis reinforced the gradual seasonal changes observed during this time of year.

This one-week study revealed a clear downward trend in temperatures, aligning with the seasonal shift from fall to winter. The data demonstrates how daily weather reflects larger seasonal changes, helping us understand the predictable nature of climate patterns in our region.