Missing Some Graphs
Handling Data Coursework
Introduction
This is based on fictional data on a school called Mayfield high school. I will be comparing two variables I have chosen to compare the relationship between the height and weight of the pupils in the school. It will be involving the following year groups seven, eight and nine. The data that I have been given to me is a secondary source, which was provided to me by teacher which was from the internet. The data has provided me with each pupils name, age, year group, height, hair and eye color, and the distance from home to school, traveling method, number of brothers and sisters and KS2 results. The aim of this investigation is to find out a relationship between two variables, the two variables which I have chose to investigate are height and weight.
Hypotheses
To test my first hypothesis i.e. as pupils get older the boys and girls get heavier and taller. I will carry out a stratified sample of 60 boys and girls. The reason why I will do a sample is because it will show the different proportions of people in each year group and gender. Therefore my data will be representative of Mayfield High School. Once I have collected the data I will then organize the heights and weights of the girls and boys in a grouped frequency table. I will then use this table to find the mean, mode, median of the results of the heights and weights of these males and females. I will then construct a cumulative frequency graph to find and locate the median, lower quartile and upper quartile. This will then be used to draw a box plot for the heights and weights of male and females. This data will be used to help me to conclude my first hypothesis.
To test hypothesis two i.e. girls in y...
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... that overall my hypothesis is correct. This is shown in the graphs of the data showing the boys and girls in year eight, nine and eleven. However in the graphs showing year seven and ten proves that my hypothesis is wrong. Also my last graph shows an overall outlook of the whole population I had sampled and it shows a very positive correlation of the taller you are the heavier you are.
To conclude my coursework I have learnt that all of my hypotheses are correct. My first hypothesis was the older you are the heavier you weigh. My second hypothesis was the girls in year seven are taller and heavier then boys in year seven. My last hypothesis is the taller you are the heavier you are. From investigating these I have learnt that the older you are the heavier you are, year seven girls are heavier and taller then boys and the taller you are the heavier you are.
There are two histograms, showing information on GPA, and showing information on final grade. Histograms are commonly used with interval or ratio level data (Corty, 2007). The data in the GPA is distributed and slightly skewed to the right, which means it has a positive skew and has a peaked distribution. The final histogram also has a leptokurtic frequency distribution, but is skewed to the left meaning this has a negative skew.
A sample of children ranging from 4 to 13 years old are going to be asked to watch a Rainbow Brite video. The children will be randomly picked from a childcare center. To ensure that the children are going to be randomly assigned, the children will range in different age groups. The first group will consist of 4, 6, and 8 year olds. The second group will consist of 10,12, and 14 year olds. It would have to be a field experiment because you have to go out and collect the data.
Obesity has become an epidemic in adults and children in the United States. Moreover, children are at risk of obesity because they do not eat enough fruits and vegetables and do not obtain enough physical activity. Also, children have a higher chance of developing health diseases related to obesity such as hypertension, high cholesterol, stroke, heart disease, diabetes and pulmonary disease. In addition, obesity in children from ages one to seventeen is an issue in Texas, since children are not aware of the serious consequences of being obese. Therefore, Texas should find ways to prevent obesity by authorizing healthier school lunches and allowing a school program to help obese children lose weight. Also, television advertisements are influencing obese children to make unhealthy choices.
Obesity in children across America has become an increasing public health concern. Obesity has been identified as an epidemic that is plaguing our children in the United States. In some countries around the world children are dying of starvation everyday. How can this happen when here in America the opposite is a major problem? This is not to say that in America there are no hungry or starving children. It has been proven that our children suffer from obesity, and “children who are overweight or obese as preschoolers are five times as likely as normal-weight children to be overweight or obese as adults” (“Hope”). Obesity not only can cause a child to become more prone to having health problems down the road, but it can also make them feel insecure about themselves. There needs to be action taken in schools as well as in homes to help prevent this growing epidemic.
The overall rate of obesity for children comes in at 17 percent, or about 12.5 million obese children in America today (Doheny 1). The number of children who are obese is growing at a fast rate. Most cases of childhood obesity are caused by eating too much and exercising too little. Extra weight puts children at a risk of serious health problems; such as, diabetes, heart disease, and asthma (Smith 1). Although obesity can be prevented, it has become a growing problem among children due to several factors that lead to health problems.
Obesity has been identified as one of the risk factors affecting directly and indirectly the health outcome of the population. Even though many approaches and programs have been conducted in order to reduce the obesity rate, this health issue is still a big headache and keeps being put on the table. According to the Centers for Disease Control and Prevention (CDC), overweight and obesity rate have been increasing significantly in the past two decades in the United States with more than 35.7% of adults and almost 17% of children and adolescents from 2-19 years olds being obese ("Overweight and obesity," 2013). As Healthy People 2020 indicated, in the period from 1988-1994 to 2009-2010, the age adjusted obesity rate among U.S adults aged 20 and over increased from 22.8% to 35.7%, which means increased by 57% while the obesity rate among children and teenagers from 2 to 19 years old increased from 10% to approximately 17%, witnessing the increase of 69% ("Nutrition, physical activity," 2013). Obesity has impact both on economic and health of the nation. Obesity is the risk factor of serious chronic diseases, including heart disease, stroke, type II diabetes, certain kinds of cancer, and other leading causes of preventable deaths ("Overweight and obesity," 2013). Moreover, obesity continues to be economic burden in terms of medical costs for either public or private payers up to $147 billion per year which increased from 6.5% to 9.1% (Finkelstein et al, 2009). In 2008, medical spending per capita for the obese or obesity related health issues is $1,429 per year, as 42% higher than “those of normal weight” (Finkelstein et al, 2009, p.8).
150 university students observed a short video of an accident that involved a white sports car and then answered 10 questions about the content on the video. One question for half of the students asked how fast the car was going when it passed the barn while the other half received a question asking how fast the car was going while traveling along the road. Just like the previous experiment, the students returned a week later with 10 follow-up questions on the video about the accident. The question asked if they saw a barn. Of the students that were asked a question mentioning a barn, 17.3% reported they had seen one. While 2.7% in the no-barn group reported they had seen it. These results for this experiment, as the others, were also statistically
Ul-Haq, Z., Mackay, D. F., Fenwick, E., Pell, J. P. (2013). Meta-analysis of the association
...body was ideal for reasons such as running faster, swimming better, and excelling at sports such as football; All of the examples listed pertaining to physical performance. They also desired to be tall in order to gain independence from their parents, and be able to do more things on their own. The boys also claimed that being tall would be useful in dangerous situations; For example, some desired a big and tall body to fight and others wanted a skinny and tall body to be able to run away from the danger. Although there was a distinction between the bigger bodies desired, and the overweight bodies, to which they gave perceived negatively. This study helps to explain the key difference between boys and girls in reguards to body image; The girls wanted to be thin in order to be beautiful, yet the boys wanted to be big and tall for reasons related to physical ability.
Childhood obesity is an increasing problem here in the United States. According to Schuab and Marian (2011) “Childhood obesity has reached epidemic proportions” (P.553). The prevalence of child obesity and overweight has increased over the last 30 years all over the United States, becoming one of the biggest public health challenges (Moreno, Johnson-Shelton, & Boles, 2013). The purpose of this paper is to give a background of the obesity epidemic, a review of current policy, and make a policy recommendation.
From the line graph I found that it was a male who made the highest
of 50 students (25 girls, 25 boys) from year 7. I have data from a
Some boys around the age of seven, are reported to believe that their male peers are better at math than fellow female students. As for girls at this age, believe that both male and female students are equally capable in math, until the age of 10. This is where female students begin to believe that males students are better in the math areas. However, during adolescence years, boys begin to agree that girls and boys are equally good at math, as girls continue to state males are more successful in math (Saucerman and
In order to be able to compare girls and boys in each year, I will
There are 44 test scores from students and I am ask to analyze the data using different methods of graph. Talk about advantages and disadvantages of each graphs lastly describing the “Middle” and the “Spread” of the compiled data and how is it significant overall. There are many different types of graphs mathematician can use to compiles data to help them get a better understanding of everything by seeing it visually before start doing all the calculation and draw conclusion. The 4 types of graphs that I am focusing on this test scores from students are Stem-and-leaf, Histogram, Pie graph, and Box-and-whisker.