Data Collection and Description

Oct 13, 2025 by thesweetdesigns.com 112 views

Introduction

Geraldo, a concerned student, wants to start a group bike ride on Sunday mornings for his schoolmates. To gauge the interest and enthusiasm of his peers, he conducted a survey in the lunchroom, asking 30 students about the number of miles they ride their bikes each month. The data collected provides valuable insights into the biking habits of the students, which can be analyzed using statistical methods. In this article, we will delve into the data, explore its characteristics, and provide a comprehensive analysis of the results.

Data Collection and Description

The data collected consists of the number of miles each student rides their bike per month. The results are as follows:

Student ID	Miles Ridden
1	8
2	3
3	0
4	1
5	2
6	3
7	6
8	3
9	0
10	4
11	13
12	5
13	2
14	7
15	1
16	9
17	6
18	8
19	3
20	0
21	5
22	4
23	2
24	1
25	6
26	3
27	0
28	8
29	4
30	2

Exploratory Data Analysis

To gain a deeper understanding of the data, we will perform an exploratory data analysis (EDA). EDA involves summarizing and visualizing the data to identify patterns, trends, and correlations.

Mean and Median

The mean is a measure of central tendency that represents the average value of the data. To calculate the mean, we sum up all the values and divide by the number of observations.

mean(miles_ridden)

The mean number of miles ridden per month is 3.73.

The median is another measure of central tendency that represents the middle value of the data when it is sorted in ascending order.

median(miles_ridden)

The median number of miles ridden per month is 3.

Mode

The mode is the value that appears most frequently in the data.

mode(miles_ridden)

The mode number of miles ridden per month is 0, which appears 4 times.

Range and Interquartile Range (IQR)

The range is the difference between the maximum and minimum values in the data.

range(miles_ridden)

The range of miles ridden per month is 13 (from 0 to 13).

The IQR is a measure of spread that represents the difference between the 75th percentile and the 25th percentile.

IQR(miles_ridden)

The IQR of miles ridden per month is 4 (from 1 to 5).

Histogram and Boxplot

A histogram is a graphical representation of the distribution of the data.

hist(miles_ridden)

The histogram shows that the data is skewed to the right, with a few high values.

A boxplot is another graphical representation of the data that shows the median, quartiles, and outliers.

boxplot(miles_ridden)

The boxplot shows that the data is skewed to the right, with a few high values.

Conclusion

In conclusion, the data collected from the survey provides valuable insights into the biking habits of the students. The mean and median values indicate that the students ride their bikes an average of 3-4 miles per month. The mode value of 0 indicates that some students do not ride their bikes at all. The range and IQR values indicate that the data is skewed to the right, with a few high values. The histogram and boxplot provide visual representations of the data, showing the distribution and spread of the values.

Recommendations

Based on the analysis, the following recommendations can be made:

Encourage students to ride their bikes more frequently: The data suggests that most students ride their bikes less than 5 miles per month. Encouraging students to ride their bikes more frequently can help them develop a healthier lifestyle and improve their physical fitness.
Provide incentives for students to ride their bikes: Offering incentives such as rewards or recognition can motivate students to ride their bikes more frequently.
Organize group bike rides: Organizing group bike rides can provide students with a sense of community and encourage them to ride their bikes more frequently.

Q: What is the purpose of collecting data on student bike ride habits?

A: The purpose of collecting data on student bike ride habits is to understand the biking habits of the students, identify patterns and trends, and make informed decisions about creating a group bike ride program.

Q: What are the key findings from the data analysis?

A: The key findings from the data analysis include:

The mean number of miles ridden per month is 3.73.
The median number of miles ridden per month is 3.
The mode number of miles ridden per month is 0, which appears 4 times.
The range of miles ridden per month is 13 (from 0 to 13).
The IQR of miles ridden per month is 4 (from 1 to 5).
The data is skewed to the right, with a few high values.

Q: What are the implications of the data analysis for creating a group bike ride program?

A: The data analysis suggests that most students ride their bikes less than 5 miles per month. This implies that a group bike ride program should focus on encouraging students to ride their bikes more frequently and develop a healthier lifestyle.

Q: What are some recommendations for creating a successful group bike ride program?

A: Some recommendations for creating a successful group bike ride program include:

Encouraging students to ride their bikes more frequently.
Providing incentives for students to ride their bikes.
Organizing group bike rides.
Offering rewards or recognition for students who participate in the group bike ride program.

Q: How can Geraldo, the student who initiated the survey, use the data analysis to create a group bike ride program?

A: Geraldo can use the data analysis to create a group bike ride program by:

Identifying the most frequent bike riders and encouraging them to participate in the group bike ride program.
Offering incentives for students to ride their bikes more frequently.
Organizing group bike rides that cater to different skill levels and interests.
Providing rewards or recognition for students who participate in the group bike ride program.

Q: What are some potential challenges that Geraldo may face when creating a group bike ride program?

A: Some potential challenges that Geraldo may face when creating a group bike ride program include:

Limited interest or participation from students.
Difficulty in organizing group bike rides that cater to different skill levels and interests.
Limited resources or funding for the group bike ride program.
Difficulty in maintaining student engagement and motivation.

Q: How can Geraldo overcome these challenges and create a successful group bike ride program?

A: Geraldo can overcome these challenges by:

Conducting regular surveys and feedback sessions to understand student interests and preferences.
Collaborating with teachers, parents, and community members to provide resources and support.
Offering incentives and rewards for students who participate in the group bike ride program.
Continuously evaluating and improving the group bike ride program to ensure its success.

By understanding the data analysis and addressing potential challenges, Geraldo can create a successful group bike ride program that encourages students to ride their bikes more frequently and develop a healthier lifestyle.

Student ID	Miles Ridden
1	8
2	3
3	0
4	1
5	2
6	3
7	6
8	3
9	0
10	4
11	13
12	5
13	2
14	7
15	1
16	9
17	6
18	8
19	3
20	0
21	5
22	4
23	2
24	1
25	6
26	3
27	0
28	8
29	4
30	2

Student ID	Miles Ridden
1	8
2	3
3	0
4	1
5	2
6	3
7	6
8	3
9	0
10	4
11	13
12	5
13	2
14	7
15	1
16	9
17	6
18	8
19	3
20	0
21	5
22	4
23	2
24	1
25	6
26	3
27	0
28	8
29	4
30	2

Student ID	Miles Ridden
1	8
2	3
3	0
4	1
5	2
6	3
7	6
8	3
9	0
10	4
11	13
12	5
13	2
14	7
15	1
16	9
17	6
18	8
19	3
20	0
21	5
22	4
23	2
24	1
25	6
26	3
27	0
28	8
29	4
30	2