introduction

Welcome to OT1102 subgroup 4's Statistics data blog. Team members: Vivien Kwa, Shermaine Lau, Feng Rui, Brenda Yap & Alicia Lim. Credits for layout: doughnutcrazy Rationale of study: to determine if an individual's BMI correlates to his/her height.

research hypothesis (H1): There is a positive relationship between an individual’s height and Body Mass Index (BMI).

null hypothesis (H0): There is no relationship between an individual’s height and BMI.

Dependent: Body Mass Index (BMI).

Independent: Height.

Extraneous: Age(Nominal), Gender(Nominal) & Timing of measurement(We measured all our subjects before lunch).

In our research, height means how tall a person is. Height is defined as the measurement of a person standing upright against a flat wall from the base of his heel to the tip of his head in centimeters (cm). Weight is taken by using a weighing scale placed on a floor in kilometers (kg). BMI is is a measure of a person's weight in relation to height.

Height is taken twice both using a vinyl measuring tape, to the nearest 0.1cm. Weight is taken twice using both a electronic weighing scale and an analogue weighing scale, to the nearest 0.1kg. BMI is calculated by taking weight in kilograms divided by height in centimeters squared times 10,000

On 1st June 2012, we gathered at Nanyang Polytechnic, School of Health Sciences, Block H, Level 5, Room 04 for our data collection. We planned to collect a sample of 30 participants with no gender preference. Participants were picked at random in a population of 55 Occupational Therapy Year 2 students. No person rejected when approached to be a subject for the data collection. Before the experiment,all 30 participants gave verbal consent to have their height and weight taken. All measurements were taken at one go, and the timing was before lunch (as food will affect the weight measurement). We used 2 vinyl measuring tape and 2 weighing scale, both analogue and digital weighing scales. Inter-rater reliability is ensured by having the measurements taken by two different group members. The measurements taken were written down on a table below.

the measuring tape was set up against the wall and made to be as perpendicular to the floor as possible. We measured 100.0cm from the ground using the measuring tape before making a mark on the wall. The 0.0cm on the measuring tape was then moved up to the mark on the wall. We did this as one measuring tape itself was not long enough to measure a person’s height. Standardization was achieved as the same one person did the setting up for both height measurement stations. During height measurement, we had the same two persons to take the measurement so as to eliminate discrepancies as much as possible. Each subject was instructed to stand with his/her back straight against the tape measure that was set up, and an appointed group member measured the height from base of feet to top of head. In order to take accurate height measurement, we used a metal ruler to mark out the height. Measurements were written down on a piece of paper and the average was calculated.

we ensured the consistency in the persons taking the measurements. The weighing stations were set up by placing both weighing scales next to each other on the ground of the room. Each subject had to step onto the electronic weighing machine first and the appointed group member had to jot down the measurement on a piece of paper. After that, the subject proceeds to step on the analogue weighing scale. The group member that was in-charge of jotting down the weight using the analogue weighing machine had to look at the scale from top down in order to reduce parallax error. Measurements were written down on a piece of paper and the average was calculated.

According to the scatter plot drawn below, there is a linear relationship between the height and the BMI variables which are both scale measurement, thus we’ve decided to use the Pearson’s r statistical test to look at the linear relationship.



Not assuming the null hypothesis, Using the asymptotic standard error assuming the null hypothesis & Based on normal approximation.

Pearson's R is 0.168, P is 0.379. Pearson's R value (<0.2) indicates a very weak relationship. Since P>0.05, we accept the null hypothesis (Ho).

We surveyed 30 subjects(n=30). After analyzing our data, we deduce that in total, Pearson's R = 0.168, p= 0.379 (>0.05). Therefore we accept the null hypothesis & conclude that there is no positive relationship between an individual's BMI and his/her height.

This statistic project has been a positive learning experience; it reinforced the concepts taught during lectures into practical application. I learnt how to analyse our data using the SPSS software to establish a relationship between our variables. In addition, i also learn how to better plan our data collection methods and ways to make sure we take the extraneous variables into consideration and that our data is as accurate and reliable as possible- we came up with a circuit to better manage the data collection - station .1height measurement by one of our team member, station 1.2 height measurement by another team member to ensure inter-reliability, station 2.1 weight measurement using digital scale and station 2.2 weight measurement using analogue scale. Teamwork is important. Besides that, what we learnt in our Research Methodology module came into handy. I feel that what we learn through this Statistics project is like a peek into our final year project and will come handy in our FYP. -Alicia.

It was definitely an interesting journey to answer what seems to be a simple question.

Statistics were but numbers to me. Little did I realise that it was much more useful.

In data collection, we had to use more than one type of weighing scale to measure how heavy a person was to ensure a more accurate measure. We had to take the measurements of a person’s height twice. I learnt how to use the SPSS software which I found essential in this project. Using the software, we could investigate if there was a relationship between the variables, the kind of relationship as well as the degree to which that relationship extended to.

This project taught me skills to deal with statistics and which I believe will be useful for the years to come as well as in my Final year project! -sher

"This statistical project has been an enjoyable yet eye-opening journey for me. At first glance, the topic that we chose looked interesting and simple to conduct. Little did I know that there were so many components to a statistical project! In the initial part of the process, we were all at a loss because we did not know how to officially embark on the project. However, after settling details such as variables and sample size, we were able to proceed with the project. The next step was to collect data and this was the part that I had the most fun. Overall, it was an enjoyable experience as I had fun in planning how to conduct the measurements. It was a little messy at the start and that left me feeling confused for awhile. However, we managed to make some changes to refine the process into a smoother one. I also realised that teamwork is very important in this part of the statistical project and that was something my group managed to achieve. After collecting the data, we had to sit down and rack our brains over the analysis of the data. I felt that the lectures and tutorials helped us to decide what to do in order to analyse our data correctly. I also realised that statistics is no easy feat, and good understanding and application of the concepts were required of us. After flipping through the notes and books, we managed to analyse our data successfully! We concluded the project by putting all our data and information into a blog. It was interesting to integrate statistics with a social site, such a Blogger. This goes to show that there are no limitations and restrictions when it comes to sharing knowledge with the world. This project has taught me a thing or two about statistics and how fun it can actually be! I also feel that this module has taught us the skills and knowledge required for our FYP in the next year. I hope you enjoyed reading the blog and cheers to many more years with Statistics!" -Brenda

I felt that during the course of our research findings, I learnt a great deal on the body mass index. Also, to be able to compute the findings on the SPSS was a tough learning process. However, with the perseverance of my group members and I, we still manage to overcome the numerous errors we faced when we try to enter our data into the SPSS. Many a time we didn't understand what our results implied from the SPSS data but I guess after using this program religiously for a week, you would eventually get a good grasp of it and analyse the results from the research findings. All in all, I had a good time working on this project with my group members and I could finally see the beauty of the SPSS program. -Vivien