Find how a child's height and weight changes between year 9 and year 10 and then see the differences in height and weight between boys and girls in year 9 and then do the same for year 10.
Maths Coursework Data Handling Project Specify The Problem And Plan I hope to find how a child's height and weight changes between year 9 and year 10 and then see the differences in height and weight between boys and girls in year 9 and then do the same for year 10. I have chosen year 9 and year 10 because in year 9 boys and girls heights and weights are still fairly similar but by year 10 a boys measurements should change considerably. Also there should be quite a big gap between the boys and girls heights but their weights should be much closer together on average. Therefore there should be quite a small gap between girls and boys in year 9 but by year 10 they should be getting wider apart. I will find these differences by finding the mean, median, upper quartile, lower quartile and interquartile range. Also I will do scatter graphs, box and whisker graphs and cumulative frequency graphs. I have chosen 42 children from year 9 and 32 from year 10 and approximately 75 children in total. I will explain why there are more from one year later. One limitation of this project is that we have to use only a sample of the year group but if we used the whole year or even the whole school our results would be much more reliable. Another limitation is that this investigation is about only one school and hence does not represent the whole nation of year 9 or 10. Furthermore the
Data Analysis Investigation-Higher Tier
By Kyle Harris Introduction During this investigation I am going to find out if boys are on average taller than girls and if their average heights are more dispersed. My hypothesis is: "On average boys are taller than girls and boy's heights are more dispersed than girl's heights." Using the data I have been provided by the school I will carry out my investigation. The data provided is based on pupils in our Co-educational comprehensive school. The data has been split up into 5 groups also known as strata; there is one strata for each year group i.e. year 7, 8, 9, 10 and 11. In turn I will look at years 7, 9 and 11 in order to test my hypothesis. During my investigation I will use stratified random sampling because it is more likely to give a sample which is representative of the population. I will use a stratified random sample of size 30 in each case. The data I will use is quantitive and continuous data. The heights of pupils are given in centimetres (Cm), correct to the nearest centimetre. In order to discover whether my hypothesis is true or false I aim to:- * Obtain stratified random samples of size 30 for years 7, 9 and 11. * Find the mean height of both males and females within years 7, 9 and 11. * Find the standard deviation (a measure of spread/dispersion.) of both males and females within years 7, 9 and 11. I will present my results using tables and
For my investigation I will be investigating the statement "Boys are taller than girls."
Investigating the statement "Boys are taller than girls." Introduction For my investigation I will be investigating the statement "Boys are taller than girls." Planning I will need to collect the year group, gender and height for each person in years 7 and 11 at Mayfield High School. I can find this information from the database the school provided. I have chosen this source of information, as it is reliable. I will use a sample size of total 120 so that is a sample size of about 60 per year group and 30 per year group per gender. This will be a fair sample as it considers a proportional number of people in each year so my results should show a similar variation in each year group therefore giving me better averages to work with. I will use this data to compare the difference in heights between boys and girls in each year group. Hypothesis My hypothesis is that I think girls will, on average, be taller than boys in year 7 as they start puberty earlier and so grow earlier. In year 11 I think boys will be taller as by this time they have started puberty and have grown taller. From the age of 14 boys generally tend to be taller than girls. So I expect my results to show that boys are taller than girls in the older age groups. Averages There are three main ways of finding an average. These are the; mean, mode and median. The mean is the most common way of finding an
Investigating the hypotheses - "Secondary school students grow taller as they grow older" and "Female secondary school students grow taller earlier before their male counterparts"
Title: Contents: Introduction: Hypothesis 1 "Secondary school students grow taller as they grow older" Hypothesis 2: "Female secondary school students grow taller earlier before their male counterparts" Course of action (COA): (This is how I'm going to prove the above) To investigate the stated hypothesis, data regarding heights of students in various year groups was collected. This data was then separated into year groups and further into gender. This data was then randomly sampled and 40 items of data were selected from each year group, 20 from the male group and 20 from the female group. total randomly sampled data items = 5 * 40 =200. NOTE: You have to show that you understand that these values are 'estimates'. For example the mean average of height for males in year 7 which we calculate after grouping the data will not be the same as the value if you add all the heights together and divide by how many you have. This is because of grouping the data. The thing is, we have to do this because of the shear volume of data we have. It is not feasible to do the former ( add them all together). You have to recognise bias. Averages, and all the other statistical shows you the trend in data, the general drift in the data, which means that they show you what the 'normal' height is in the whole of each year group. Bias is when the statistics do not represent the data. They
An Investigation Into Weight, Height and IQ of Students At Mayfield High School.
An Investigation Into Weight, Height and IQ of Students At Mayfield High School From the data I have been given I aim to prove two things . The taller the person the heavier they are - I think this because when a person is taller they generally have a larger mass and with the analysis of the data I will hopefully be able to see Which students are over or under weight 2. That girls generally have a higher IQ than boys To start with I shall have to take a sample of the data of years 7, 9 and 11. I shall do this because there is too much data, so I shall take a sample to make the figures more manageable, it shall be a random sample to make sure that it is an unbiased. To do this I shall take data by using the random button key on my calculator. I therefore created a this sampled table of data: Year group Forename Gender IQ Height (M) Weight (Kg) 7 Luke Male 03 .60 38 7 Rhys Male 90 .51 45 7 Jospheh Male 08 .50 51 7 Billy Male 06 .43 41 7 Paul Male 05 .53 45 7 Lauren Female 06 .32 35 7 Maggie Female 16 .49 53 7 Jessica Female 97 .60 42 7 Angela Female 00 .47 44 7 Rebecca Female 02 .52 52 9 John Male 02 .80 64 9 Andrew Male 12 .82 66 9 Jordan Male 04 .70 47 9 Arthur Male 99 .71 68 9 Zac Male 00 .80 51 9 Natalie Female 97 .50 45 9 Jade Female 94 .57 48 9 Mary Female
Obesity and height and weight
Maths Statistics Coursework - Mayfield High School Introduction: I have been approached by my local council who would like to try and gain a better understanding of obesity in the local community. The body mass index is the universal measurement of whether a person is overweight. They are trying to decrease the number of future cases of obesity and therefore, I must look at the future generation of adults, so I will take this case back to its origin, I will take it back to school. All the data that I require for this project will be provided by the council. All results are from a local school called "Mayfield High School". body mass index = weight/height² Phase A: As 1180 pupils is an extremely large number to work with, I have decided that I will carry out a sample. The type of sample that I will carry out is called a stratified sample. This means that I will arrange them all in the order that I am going to investigate, and then keep deleting entries and save every nth term. I have done this so I get a nice small sample which is easy to work with, and most importantly, represents the data that I am dealing with. Sampling is more efficient and takes less time than using all the data. After carrying out my sample and ending up with 100 statistics, I created an extra column in my table called BMI (body mass index). I felt that using the body mass index would be a more
Driving Tests
Driving Tests Histogram analysis: Statistics for male minor mistakes made Statistics for female minor mistakes made Grouped Data Statistics: Grouped Data Statistics: Total Frequency, n: 40 Total Frequency, n: 40 Mean, x: 13.125 Mean, x: 13.4375 Standard Deviation, x: 8.28685 Standard Deviation, x: 7.36732 Modal Class: 0- Modal Class: 10- Lower Quartile: 6.25 Lower Quartile: 8.33333 Median: 12.5 Median: 13.0769 Upper Quartile: 18.3333 Upper Quartile: 17.5 Semi I.Q. Range: 6.04167 Semi I.Q. Range: 4.58333 Male: My histogram displaying the number of minor mistakes made by my male sample shows quite an obvious pattern. The first three columns are all very tall, this would imply that the majority of males in my sample completed their driving test with less than half of the possible amount of minor mistakes awarded. Although it is difficult to say whether this majority of drivers in the first three columns made mistakes at the bottom or the top end of the described range. This difficulty is also present if any column on its own is taken into consideration. Starting with a tall start the histogram displays a sharp drop after the third column. Histogram
On average, I predict that's boys will be taller than girls.
Mayfield High School The idea of this project is to compare students' data. The pupils that will be used are from Mayfield High School (renamed to protect data), ranging from years 7-11 and will be boys and girls. A lot of data has been collected from the school, ranging from age to the distance they travel to school. The project will attempt to reach conclusions regarding three specific stages. In answering these stages a range of sampling methods, presentation of data, and statistical calculations will be used in order to interpret and evaluate the data and come to a valid conclusion, drawing together all the data. Each stage will be presented and it will be explained what statistical methods will be involved in drawing conclusions for these questions. Hypothesis 1: On average, I predict that's boys will be taller than girls This involves taking one piece of data from 30 boys and 30 girls randomly. I decided to choose the height of 30 boys and 30 girls as this should give me a varied result helping me draw accurate conclusions about the data. I will then calculate the mode, mean, standard deviation, draw histograms, box-and-whisker plots, and cumulative frequency curves and then calculate the median and the range. Initially I need to sort the data in Microsoft Excel into 2 groups, one of male and one of female. To do this, I highlight all of the data and click on the
The hypotheses I have to find out are the following:Boys are taller than girls The taller you are the heavier you are The more television you watch the larger the body mass index
Statistics Coursework This piece of coursework that I am doing is look at relations between height, weight, gender and Body mass index of Mayfield High School. I will do this by taking a sample of 118 out of 1183 students. The hypotheses I have to find out are the following: . Boys are taller than girls 2. The taller you are the heavier you are 3. The more television you watch the larger the body mass index. I will use the data given by my teacher and then do a stratified sample. I am doing the stratified sample so that I can get the right proportion sample for each year group. Using my calculator, I choose a random number between 1 and 10, and then go down for whatever number it is. For example, if the random number was 8 and there were 141 boys/girls in the year group I would choose the numbers 8, 18, 28, 38...38. Then I will use systematic sampling to get the right amount of people in each year group. The calculations for each year using the stratified sample are in the following: Year 7 Girls: 131 x 118 ? 13 1183 Year 7 Boys: 151 x 118 ? 15 1183 Year 8 Girls: 125 x 118 ? 12 1183 Year 8 Boys: 145 x 118 ? 15 1183 Year 9 Girls: 143 x 118 ? 14 1183 Year 9 Boys: 118 x 118 ? 12 1183 Year 10 Girls: 94 x 118 ? 9 1183 Year 10 Boys: 106 x 118 ? 11 1183 Year 11 Girls: 86 x 118 ? 9 1183 Year 11 Boys: 84 x 118 ? 8 1183 For my pilot questionnaire the
Mayfield High. I am going to investigate the relationship between the height and weight of the pupils. I will be investigating how height and weight affect each other. For example, if an increased height means an increased weight.
Coursework: Mayfield High Mayfield High: Maths coursework I am going to investigate the relationship between the height and weight of the pupils. I will be investigating how height and weight affect each other. For example, if an increased height means an increased weight. Before I begin, I predict that the correlations for all of my graphs will be positive. The reason for this prediction is because I know that as your height increases so does your weight. After deleting what I found, I deleted all columns except for 'Year group', 'Gender', 'Height' and 'Weight' on both the 'KS3' and 'KS4' sheets on the excel, since they were not needed to work out the relationship between height and weight. Then, using the above table, I calculated 40% of each of the numbers inside it, for example, Year 7 girls: 131 x 0.4 = 52. The reason that I chose to use a sample of just 40% is because using all of it would clutter my graphs too much. I did, however, want of all my samples to be above 30, as this would provide enough information to create the graphs. From this I counted the resulted number of people of each gender and year group and coloured them red, deleting the rest, as they were not needed. The reason for this is because I am using a stratified random sample; this is because it collects a certain percentage of each section that gives a good estimate to represent everyone's views.