ระยะทางส่งผลต่อปัจจัยใดบ้าง-Probability and Statistics
Summary
TLDRThe presentation investigates how the distance from students' homes to the university impacts their financial situation, focusing on computer engineering students. Through data collected via Google Forms, the study analyzes responses from 40 participants, assessing average distances, monthly expenses, and correlations between variables. Results show that greater distances lead to increased travel costs and may negatively affect financial health. The study supports a GPA above 3.0 but finds no evidence that average monthly expenses exceed 8,000 THB. Overall, the findings highlight significant relationships between residence distance and financial outcomes.
Takeaways
- 😀 The project investigates the impact of students' current living distance on their financial situation.
- 😀 Data was collected using Google Forms from 60 students, ultimately analyzing 40 responses.
- 😀 The average distance from home to university is 10.57 km, with a median of 3.75 km.
- 😀 The average monthly expenditure reported is 7,784.75 THB, with a median of 7,000 THB.
- 😀 Statistical analysis was divided into descriptive statistics and computation, including goodness of fit tests.
- 😀 The data shows an exponential distribution for living distance, travel expenses, and monthly savings.
- 😀 Correlation analysis reveals negative relationships: as living distance increases, total income decreases.
- 😀 The research indicates that students living closer to the university have lower travel costs.
- 😀 There is a positive correlation between distance and overall expenses, suggesting increased costs with greater distance.
- 😀 The project concludes that living distance affects students' financial dynamics, particularly their travel expenses.
Q & A
What is the main objective of the project presented by the group?
-The main objective is to study whether the distance from current residences affects the financial situation of students at the university.
How did the group collect data for their analysis?
-The group collected data using Google Forms, gathering responses from students about their distance from the university and their monthly expenses.
How many students participated in the survey?
-A total of 60 students completed the survey, but the group analyzed data from 40 of those responses.
What are the two main sections of the analysis outlined in the presentation?
-The analysis is divided into two main sections: descriptive statistics and distribution, and computation, which includes goodness of fit, correlation, and hypothesis testing.
What was the average distance of students from their residences to the university?
-The average distance was reported to be 10.57 kilometers, with a median distance of 3.75 kilometers.
What were the findings regarding the distribution of the data collected?
-The analysis found that the data for distance, monthly expenses, and savings were all distributed exponentially.
What was the conclusion regarding the GPA of engineering students from years 2 to 4?
-The study concluded that the average GPA of engineering students from years 2 to 4 is greater than 3.0.
How does the distance from home affect monthly expenses according to the correlation analysis?
-The analysis found a negative correlation, indicating that as the distance from home increases, monthly expenses decrease.
What is one significant relationship identified in the correlation findings?
-One significant relationship identified was that students living closer to the university had lower transportation costs compared to those living further away.
What recommendations did the group provide based on their findings?
-The group highlighted the importance of considering location in financial planning for students, suggesting that living closer to the university may lead to lower expenses.
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