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# Investigating the Relationship Between Weight and Height among Providence Island's Residents

This Data Analysis assignment presents a comprehensive study in which we delve into the intriguing relationship between weight and height among the diverse residents of Providence Island. Understanding this connection is vital, as it provides valuable insights into the health and body composition of individuals. Our research aims to contribute to the existing knowledge in this domain, offering potential benefits for healthcare professionals and policymakers. With meticulous data collection, analysis, and visualization, we unveil a compelling positive correlation between weight and height, shedding light on how these two variables intersect in the context of health and well-being. Explore the results and draw your conclusions from this fascinating exploration.

## Problem Description:

The primary focus of this study is to comprehend the correlation between an individual's weight and height, particularly among the population of Providence Island. This is a crucial aspect as it provides essential insights into the overall health and body composition of individuals. Furthermore, this information can be highly beneficial for various applications, such as evaluating nutritional status, devising effective weight management strategies, and recognizing potential health risks linked to weight and height variations. Through this comprehensive investigation, we aim to expand the existing knowledge in this domain and, in turn, provide valuable insights for health practitioners and policy makers.

## Variables:

Response Variable: Weight (continuous)

Explanatory Variable: Height (continuous)

Methods:

• Sampling Strategy: A straightforward random sampling approach was utilized to gather a sample of residents from Providence Island. This method ensured that each resident had an equal opportunity to be included in the study. Employing a random number generator, each resident received a unique identifier, and subsequently, a sample of 36 individuals was randomly chosen to form the study sample.
• Population of Interest: The scope of this study extends to encompass all residents of Providence Island. The collected sample aims to be representative of the broader population residing on the island.
• Data Collection: Data collection was carried out across different towns on Providence Island, specifically in Nelson, Takazaki, Hayarano, and Shinobi. The data collection procedure involved visiting these areas and approaching households to request their voluntary participation in the study. Informed consent was obtained from the participants, or from their parents/guardians in cases involving minors. The information recorded for each participant included the town name, individual's name, age group, weight (in kilograms), and height (in centimeters).
• Study Type: The study employed an observational approach, meaning that data concerning weight and height was collected without any form of intervention or manipulation. The primary objective was to delve into the relationship between weight and height among the inhabitants of Providence Island.

## Data:

Table 1: Data of Weight and Height among Inhabitants of Providence Island

S/No Town Names Age group Weight (Kg) Height (cm)
1 Nelson Jamie Wilson 18 71.4 173.4
2 Nelson Dianne Morrison 27 43.7 152.8
3 Nelson Nicolas Gagnon 26 79.7 187.3
4 Nelson Ruby Collins 15 63.7 166.6
5 Nelson Zachary Price 1 9.4 81.5
6 Nelson Aahna Kaur 22 75.7 170
7 Nelson Lila Collins 14 39.3 151.6
8 Nelson Hayley Johnstone 16 55.3 168.6
9 Nelson Yuka Wilson 17 76.8 169.3
10 Takazaki Nico Sorensen 14 53.6 161.2
11 Takazaki Robin Morris 15 63.8 170.2
12 Takazaki Julian Eklund 19 82.9 175.6
13 Takazaki Percy Lemaitre 14 60.7 171
14 Takazaki Madison Collins 10 39.9 141.8
15 Takazaki Noah Connolly 19 63.3 172
16 Takazaki Elise Erickson 22 50.9 163.4
17 Takazaki Felix Pallesen 15 82.6 175.4
18 Takazaki Matthew Connolly 15 59.4 173.4
19 Hayarano Klya Mccarthy 9 37.8 145.9
20 Hayarano Hanne Sorensen 15 48.6 166.3
21 Hayarano Vladimir Riedel 8 32.2 133.9
22 Hayarano Elsa Sorensen 12 50.8 155.3
23 Hayarano Souta Connolly 17 81.1 175.7
24 Hayarano Nathan Connolly 5 19.6 118
25 Hayarano Chota Yamada 18 72.8 176.4
26 Hayarano Chloe Regan 18 62.8 170.2
27 Hayarano Garthy Ganier 8 30.9 127.5
28 Shinobi Lucinda Carlsen 8 25.4 128.4
29 Shinobi Raum Lund 14 52.6 173
30 Shinobi Brenda Blomgren 11 44.9 148.9
31 Shinobi Lars Solberg 10 50.8 148
32 Shinobi Alicia Abbasi 8 30.1 128
33 Shinobi Olson Lund 17 56.7 173.3
34 Shinobi Satoru Watabe 5 21 109.8
35 Shinobi Sebastian Scholz 18 67.2 169.6
36 Shinobi Beau Morris 12 44.5 160.6

## Results:

Table 2: Sample Statistics of Weight and Height among Inhabitants of Providence Island

Statistics Weight (Kg) Height (cm)
Minimum 9.4000 81.5000
Q1 39.7500 147.5000
Median 53.1000 166.4500
Mean 52.8306 156.4972
SD 19.2239 22.7250
Q3 64.6500 172.2000
Maximum 82.9000 187.3000

Figure 1: Scatterplot of Weight and Height among Inhabitants of Providence Island

The scatterplot vividly illustrates a robust positive linear relationship between weight and height among the inhabitants of Providence Island. While individual data points show some variability, the overall trend is clearly upwards, signifying that as weight increases, height also tends to increase. The scatterplot strongly confirms the positive association between weight and height within the dataset.

## Summary and Discussion:

The sample statistics and the scatterplot contribute critical insights into the intricate relationship between weight and height among Providence Island's residents. The mean weight of the sample hovers around 52.83 kg, with a standard deviation of 19.22 kg. In parallel, the mean height is approximately 156.5 cm, with a standard deviation of 22.73 cm. This evident correlation between weight and height implies that individuals with higher weights also tend to be taller. However, it's imperative to acknowledge the potential influence of age as a confounding variable. Age can significantly affect both weight and height, especially in the context of growth and development. Younger individuals may exhibit lower weights and heights in comparison to their older counterparts. Therefore, to account for this potential confounder, it is essential to incorporate age as a variable and analyze its influence on the weight-height relationship.

## RStudio script:

```Data <- read.csv("Height.csv") summary(Data\$Weight) sd(Data\$Weight) summary(Data\$Height) sd(Data\$Height) plot( Data\$Weight ~ Data\$Height, main = "Relationship between Height and Weight", xlab = "Height (cm)", ylab = "Weight (Kg", col = "blue", pch = 16, cex = 2, lwd = 1.5, bg = "lightblue" )```