Mayfield School Mathematics Statistics Coursework
Is there a link between ability in Maths and ability in Science? Introduction I would like to know whether there is a link between ability in Maths and in Science in the Year 7, 8 and 9 students at Mayfield High School. My initial thoughts are that there is a link between the two because Maths and Science share some of the same attributes - they both involve formulae, they both require logical ability, and they both use numbers. Furthermore, I think that someone with an interest in Maths will also have an interest in Science, and so will probably work hard at both. Data Collection To investigate this link, I will use the Key Stage 2 results from the Mayfield High School database. There are 813 Year 7, 8 and 9 students listed in the database, so to save time I will base my investigation on a sample of 30 of these students. Bias is anything that occurs when taking a sample that might prevent the sample from being a true representation of its parent population. To avoid bias, I will ensure that my selection of the sample is completely random. To ensure a random selection, I will use a random number generator on my calculator. In the database, the students are numbered from 1 to 813. As the random numbers appear on my calculator, I will record the associated data in two or three tables, once for all 30 students, one just for males and one just for females. I have decided to
AS Psychology Observational Study Of Refectory Behaviour.
AS Psychology Observational Study Of Refectory Behaviour. I am going to conduct an experiment to observe the type of food purchased buy the members of Braintree College. I shall conduct my experiment with a team of peers and we shall conduct the experiment retaining discretion. Hypothesis: "Females buy more sandwiches in the college refectory" Aim. From my one tailed hypothesis you can see that my aim is to observe whether females purchase more bread-based products e.g. sandwiches, rolls and baguettes from the college refectory, during a standard thirty-minute break. Subjects. Our subjects were people who have a connection with Braintree College and who were buying products for consumption from the college refectory. There is no way we could be sure that everyone that we observed was actually part of the college, but for our observational experiment there was no way in which we could over come this problem and no way in which it should effect our results. Materials Our data-recording sheet was a table consisting of two columns with separate male and female sides. We kept a tally as to who purchased bread based products. This was the easiest and most efficient data-recording sheet we designed as it enabled us to collect the data quickly and discreetly. Final data recording sheet. Females purchasing Bread-based Products Males purchasing bread-based products. 7 5
Investigating Gender Differences in Helping.
Investigating Gender Differences in Helping. Aim: To find out whether subjects will help opposite gender students faster than same sex helper would. Introduction: Altruism is a form of pro-social behaviour in which a person will voluntarily help another at some cost to themselves. The primary motivation for altruistic behaviour is seen as a desire to improve the welfare of another person rather than the anticipation of some reward or for any other reason that might indicate self-interest. One of the major problems for psychologists has been determining what is truly altruistic and what might be better explained in terms of egoism. Batson et al.'s (1997) empathy-altruism hypothesis proposes that empathic concern evokes an altruistic motivation. Studies supporting this hypothesis have systematically varied whether individuals can only obtain egoistic goals by helping, or whether they can escape from the situation and obtain the egoistic goals without helping. These studies demonstrate that at least some people have helping intentions that are not explained by egoistic motivations, such as the relief of personal distress, escaping public shame for not helping, the relief of sadness, and the desire to make oneself happy. In one study, Batson et al. (1981) used a placebo drug which had no real effects but would led participants to interpret their reactions as high or low empathy.
Guesstimate lines and angles
Guesstimate Introduction All pupils in Yr7 and Yr10 were asked to guess the length of a line and the size of an angle. I will be looking and investigating the results between the in yr 7 and the results from yr 10. Hypothesis * Age ~ The group of Yr10's may measure the line and angle more accurately because they have been in education for longer and have more practice. * Gender ~ The girls may measure the line more accurately because its proven that girls try harder in schools than boys. Plan The raw data for this experiment has been collected for me, this is called secondary data. If I was to collect the data myself this would be known as primary data. From my raw set of data I will be selecting what results I am going to use by the method of Random sampling. I will be doing this by giving the set of results a number and then from that I will press the 'random' button on the calculator. This will then determine what results to use from the table. I chose this method because I thought it was the fairest, other methods of sampling include: * Systematic sampling - Samples taken in a periodic and regular fashion. The periodicity may be distances in 1, 2, and 3 directions, in regular angular increments, or in any other periodic fashion. * Stratified sampling - the results are divided into subpopulations and random samples are taken. * Cluster Sampling - the results
we can see if there is any correlation between a person's height and weight because if no correlation is present: Mayfield High School
Data handling coursework: Mayfield High School Mayfield School is a secondary school of 1183 pupils aged 11-16 years of age. For my data handling coursework, I am going to investigate a line of enquiry from the pupils' data. Some of the options include; relationship between IQ and Key Stage 3 results, comparing hair colour and eye colour, but I have chosen to investigate the relationship between height and weight. One of the main reasons being that this line of enquiry means that my data will be continuous (numerical), thus allowing me to produce a more detailed analysis rather than eye or hair colour, where I would be quite limited as to what I can do because the data is discrete. I think that this will be a more varied investigation unlike the relationship between eye colour and hair colour, as it is pretty random which colour eyes and hair you have and does not have anything in common. All the information given to us is too much to use, and therefore I have selected only a small amount of data for each student, which will be relevant to the height and weight of each student. My variables only looking at height and weight so I have deleted all the other variables besides: name, age, gender, height, weight together with method of getting to school, how far away they live from school and favourite sport since I could use all the information to extend my enquiry and could be
Video Games are profoundly sexist, and largely reflect a dominant ideology, which reinforces unequal power relations men and women. Agree or disagree, use at least 3 examples.
NAME Louise Alexander NO. s1545100 SUBJECT Video Games Culture CODE 3411FMC TUTOR David Cox ASSESSMENT Item 3 - Culture Issue Essay WORD COUNT 2,082 words DATE 30th May 2003 QUESTION: Video Games are profoundly sexist, and largely reflect a dominant ideology, which reinforces unequal power relations men and women. Agree or disagree, use at least 3 examples. As the popularity and accessibility of video games continues to increase, the question of the effect of the portrayal of women in video games arises. Also, the roles of males and females in this text, and how they differ from one another. The idea of male dominance in video games is demonstrated by these traits: expectation that males should be tough, brave, and aggressive; exclusion of women as a powerful force; and frequent quarrelling and fighting1. A wide variety of media messages can act as teachers of values, ideologies, and beliefs and can provide images for interpreting the world. This paper illustrates that the video games that are being played by today's society present an overwhelmingly traditional and negative portrayal of women and that the development of gender identities and expectations (especially among youngsters) may be affected by these portrayals. For example, girls may expect that they will continue to be victims and needy and that their responsibilities include maintaining beauty
Maths GCSE Handling Data Coursework Mayfield High School - Year 10 & 11
Maths GCSE Handling Data Coursework Mayfield High School - Year 10 & 11 For my statistics coursework I am going to investigate the relationship between the height and the weight. I will use a wide range of mathematical techniques to present my data and findings in different ways. I will also focus to test my hypothesis which is: As the height increases the weight increases and also the relationship between these the height and the weight will become stronger as they get older. I also think that there will be a difference in this between the boys and the girls. The table below shows the number of boys and girls there are in each year group: Year Group Number Of Boys Number Of Girls Total 0 06 94 200 1 84 86 70 Total 90 80 370 For my project I will take a random sample of 30 students. I will use the random sample button on a calculator to do this. Year 10 No of boys: (106/370) x 30 = 8.5946 ˜ 9 No of girls: (94/370) x 30 = 7.6216 ˜ 8 Year 11 No of boys: (84/370) x 30 = 6.8108 ˜ 7 No of girls: (86/370) x 30 = 6.9730 ˜ 7 Total number of students = 31 As I just need 30 students I need to get rid of any one student In Yr 10 boys 0.4054 is needed to get 9 In Yr 10 girls 0.3784 is needed to get 8 In Yr 11 boys 0.1892 is needed to get 7 In Yr 11 girls 0.027 is needed to get 7 Therefore it's better to get rid one Yr 10 boy to get my sample of 30
We read a poem called the
John Updike: Alfred A. Knoff, Inc. 1990. Good. in Good dj. Fiction xlib., usual library markings.,clean pages., In John Updike's fourth and final novel about ex-basketball player Harry "Rabbitt" Angstrom, the hero has acquired heart trouble, a Florida condo, and a second grandchild. His son, Nelson, is behaving erratically; his daughter-in-law, Pru, is sending out mixed signals; and his wife, Janice< decides in midlife to become a workin g girl. Through the winter, spring, and summer of1989, Rabbitt explores the bleak terrain of late middle age, looking for reasons to live. The geographical locale is divided between Brewerin southeast ern P., and Deleon in southwestern Florida. First Trade Edition. Binding is Hard Cover. Fiction FICTION NOVEL 0394588150 504910 A Loss of Motivation In English Seven we read a poem called the "Ex Basketball Player" by John Updike. The main character's name was Flick Webb. The poem explains how Flick lost motivation. In high school Flick was an excellent basketball player, if not, the best. After high school Flick didn't continue his basketball skills, and he never had tried as hard on his academics as he did on basketball. Flick now works at Berth's Garage and has a dead end life. I think that Flick gave up because he didn't want to work at something that didn't come easily, such as academics. I enjoyed this poem because it makes you think, I
The investigation that I am going to conduct is to see if peoples Height is related to their Age
Data Handling Introduction The investigation that I am going to conduct is to see if peoples Height is related to their Age. Plan I. Outline my goals and what I am trying to prove. This will enable me to predict my results (hypothesize) II. Collect data from various resources. III. Review the data, making sure it is unbiased data. IV. Put the raw data into tally charts. V. Then break down into separate ages (11 through to 17) VI. Produce cumulative frequency graphs for each age (inc. quartile ranges and median) VII. Calculate the mean for each age group and find out the standard deviation for the data. VIII. Conclude your investigation. My Hypothesis: I believe the older you are, the taller you are in height. I believe this because during the ages 11-17 there is a definite increase in height and the person is most likely to continue to grow further, whilst he or she's gets older. Collecting Data The data has that I have collected has been provided by the census at school website. The data that I collected has gone through a random sampling to assure that the data was not biased in any way, also the data has not been changed in anyway it is an accurate representation of the general population between the age of 11-17. This data will be included as a reference in my coursework at the end. Tally Charts The data at the moment is just raw data; I am going
This Investigation is to see if there is a correlational relationship between individuals G.C.S.E grades and their AS-Level grades, hence also individuals ability to adapt to a higher volume of more difficult study.
Maths Coursework - Statistics Aims This Investigation is to see if there is a correlational relationship between individuals G.C.S.E grades and their AS-Level grades, hence also individuals ability to adapt to a higher volume of more difficult study. This is a particularly relevant area to research as I am currently studying at Sir John Deanes College in Northwich. I am interested in seeing how well individuals do at a higher level of education, when they are often under a higher degree of pressure due to other aspects of life. Data Collection In this investigation the population is the students who attend Sir John Deanes College in Northwich. As this is a large college a sampling method clearly needs to be used. When I originally collected my data I obtained information from two Art classes, two Maths classes and two English classes, in effort to obtained results from students who excelled in different academic areas. Once this data was obtained I stratified these 66 results into 50 results, representative of the number of participants originally sampled. Sampling 50 Participants data needed from the original 66 obtained, the sum to calculate how many of each were needed is: (Subject total/Overall total)*50 No. Needed English 8 Maths 8 Art 4.3 N.B. Maths number rounded up to give 50 data sets, this was done as the maths figure was the closest to being rounded.