MAYFIELD HIGH SCHOOL Aim During this project I will be examining the relationships between the attributes of the pupils of Mayfield High School; all attributes are presented in the data sheet. My aim is took produce a line of enquiry which has two or more statistics regarding the pupils which are related to each other. An example of a possible line of enquiry could be to investigate the question "Could the average number of television hours affect the key stage results". Line of Enquiry My line of enquiry is "Does an increase in IQ (intelligence quotient) mean a higher Key Stage Result (depending on what Year you are in)." I have selected these attributes because I think they have a strong link between each other. IQ is a test of general knowledge therefore affects someone's ability on how well they do in Key Stage exam. Structure of investigation . Hypothesis 2. Collecting Unbiased Data 3. Evidence: * Graphs * Tables * Diagrams 4. Evaluation . Hypothesis The line of enquiry I will be investigating is: "Does an increase in IQ (intelligence quotient) mean a higher Key Stage Result (depending on what Year you are in)." I predicted there would be a link between the two quantities. I consider this because IQ means your general knowledge; therefore the higher figure of IQ indicates higher ability of understanding. KS exams are
Maths Coursework Data Handling Task Statistics Data In this piece of coursework I have been set the task to find out about the students in our school. I need to prove the following hypothesis: 'Pupils in Band A perform better than pupils in Band B' I must suggest whether the hypothesis is correct or incorrect. I will do this by comparing Band A with Band B in the following areas: * Mean averages from key stage three- (level tiers 3-5, 4-6, 5-7) * Range of scores * Modal and median of the scores. There are many different techniques and methods which I can use to solve my above problem. I will use some techniques which will enable me to work out means, ranges, modes and medians of scores. To help me with my work I could also use cumulative frequency graphs, box plots and interquartile ranges. These will all help me to compare the differences between the two bands from looking at their scores. I am going to focus on 96 pieces of data (pupils) which I shall be analysing the levels and scores of both bands A and B. The first thing that I am going to do is, to compare the overall results from both bands regarding their scores from a maths SATS paper. This would involve me using a process called stratified sampling. This basically involves me reducing the amount of data that I need to compare. This method is seen as time consuming on a very large scale of data, which
Maths Statistics Coursework Yr10 Correlation between: The more hours spent in the gym the more amount of weight you will loose. Explanation on correlation This is a scatter graph on the following correlation and is a positive correlation between the more hours you will spend in the gym the more weight you will loose. This shows that if people stay healthy then they would weight less. I will now work out the mean, mode and median of certain numbers to prove the correlation and prove that the correlation is correct. I will also be having a stem and leaf diagram and a inter quartile range which will also prove my correlation. Firstly to prove that my correlation is positive and is correct I will create a stem and leaf diagram which is a diagram that shows data in a systematic way and the mode median and mean can be found easily from this. Once the stem and leaf diagram is created I can then find the average, mean, mode and median of the correlation. Stem and leaf Diagram Gym hours Weight 2468 0 024 2 3 4 5 04567 6 02345 7 02478 8 4689 9 048 This is the stem and leaf diagram for the correlation between gym hours and weight, finding the mean, mode and median should be much easier now. Average of Gym hours (D2:D17) =-3.375 Average of weight (E2:E17) = 63.25 That is one way of finding an average to support the correlation between gym hours and
Data handling coursework Introduction For this coursework I am going to ask 25 males and 25 females to estimate a line and an angle. Once they given an estimate of the line and angle I record the data onto a spreadsheet. From this I will create graphs and I will work out the mean median and other things. I am going to analyse my graphs and charts according to my hypothesis. Factor considered I think there is a relationship between estimating angle and lines. People tend to be more accurate on estimating lines because people are more focus on it rather than when they are estimating angles they less concentrate. Another reason is that the understand lines much better than angles. The factors that affected a person's ability to estimate the angle or line are states below:- * Age -An elder person would have more experience in doing things than a younger person. Example younger people won't be accurate in estimating angles than older ones this would be because they have less experience & skill, therefore the percentage error will be less for an older person than a younger one. However an older person can have visual problems as they get older so this could e a factor against older people * Gender- People have stated that females are better than males in doing certain things. Example females would be more precise in estimating lines and angles. For this reason, this would be
Plan I am going to investigate into factors about people's lives affecting and linking to I.Q. My hypothesis is that people with a higher I.Q watch less hours of television a week, have less siblings and received good Key Stage 2 results. I am investigating this line of enquiry because I am interested to see the correlation, if any, between I.Q, the amount of television watched and the number of brothers and sisters people have. Also I believe people with a higher I.Q would be more intelligent, therefore receiving higher Key Stage 2 results, and would like to see whether I am right or wrong to believe this. I assume they would watch less hours of T.V a week if they have a higher I.Q, as I believe they would be spending more time doing homework and revision. Also I think the higher the I.Q the less siblings they will have because I think they would receive more encouragement from their parents. I aim to avoid bias in my investigation by following certain sampling methods. However there are some factors that could still cause bias that I cannot change/prevent for example if there are errors in the population or dishonest answers as the data I am using is a census questionnaire. Also some key stage 2 results have been left blank, therefore I am going to assume that all blank fields equal nothing which could be caused by them not taking the exam, so this may effect my results and
WHAT ROLE DOES INTELLIGENCE PLAY IN EARNING POTENTIAL? Candidate: Sergei Perfiliev Date: May, 2005 Area: Psychology Supervisor: Christian Bryan Word Count: 3899 words Abstract: This study established an extent that intelligence has on earning potential of an average individual. The paper, first, discussed the meaning of the term intelligence and how it is quantified. Since the intelligence is a complex aspect, the essay separately focused on elements that make it, such as IQ and EQ, and then by examining psychological researches' data, analyzing statistics, case examples and surveys on each element, it brought IQ's and EQ's analyses together and reached the conclusions concerning intelligence as a whole. Intelligence is reinforced by nature and nurture. IQ is measured through IQ testing and AFQT. EQ is quantified by self-report essays and by MSCEIT testing. Individuals with higher IQ do tend to earn more, but IQ's overall influence is little, still not negligible. EQ serves as a better predictor of earning potential than any other factor and influences future income to the great extent. Therefore, combined IQ and EQ factors, which make up intelligence, play a very significant role in shaping the future earnings on individual. Other factors, such as luck and social, family backgrounds play a much lesser role than intelligence in predicting one's earning potential. The
For my investigation, I am going to see if there is a similarity between the number of hours watched of television per week and their personal IQ for year 10's and 11's in key stage 4.
Maths Coursework Introduction and Hypothesis For my investigation, I am going to see if there is a similarity between the number of hours watched of television per week and their personal IQ for year 10's and 11's in key stage 4. I am trying to prove that the less television they watch, the higher their IQ will be as TV time means less time for school work. I downloaded the data from the Internet (from edexcel) and I copied the information on to the Excel spreadsheet. Method Firstly, I will create a graph (scatter graph) to see if there is a difference between the number of hours watched of television per week and their personal IQ of both males and females together. The formula for the line of best fit (trend line) will identify if there is any relationship. The closer the integer in front of the 'x' is to zero, the less there is any correlation. I will then split up the data into males and females and repeat the process drawing scatter graphs for each and comparing the slopes hence the relationship. At this stage, I would like to look at the distribution of males and females in these years. As it is easier to compare the data visually, I will use the function facility on the spreadsheet to calculate the maximum, the minimum, the lower and upper quartiles and the median. I will use these values to draw box plots. I will also use a method called 'Stratisfied sampling'
Comparison of SATs results to obtain statistical data on students. Introduction. I have chosen to look at the school's SATs scores for the past three years. I decided to choose this topic as I felt hat it would be interesting to compare the results, also I thought that the topic would give me some good data to work with. I thought that it could be possible to compare scores between sexes, if the scores on average have changed either better or worse. As well, I thought that it would be interesting to see if there is any correlation between subjects and their scores. Data. The data that I am using is past SATs scores from the schools records, over three years. I decided to use three sets of data so I can compare several years of results, this will enable me to get average scores over all three years for both male and female and also an average of all scores, using three years worth of data will also allow me to have more data to work with. I think that the way in which I got my data, which was taking them straight from the school's records, is best because many students would not know/remember their scores; I can receive as much data from each year as I want without much hassle or time wasted. Also this way eliminates the possibility that the data that I received is false, as students may wish to say that they got better or worse scores than they actually did. The data
Bivariate Data I am going to carry out an investigation into a set of bivariate data. The data I will investigate are a previous year groups KS3 and GCSE point score averages. I will see, whether or not there is a correlation between the KS3 and GCSE result scores. By finding a correlation or not, I will be able to determine if the scores obtained at KS3 will allow teachers to predict the student's score at GCSE. If there is a strong correlation, this will be very useful for teachers and students to give them an idea on what they can be expected to score. Grade Predictions would be easier and probably more accurate. For example, if there is a correlation, a student could predict their GCSE score by using the KS3 results they obtained, and with this would provide a target score to reach or beat. This will also be useful for the teacher where they will be able to overview any additional help or teaching that a student may or may not need. The Population (presented in table 1) shows last year's groups, KS3 and GCSE point score averages. There are a total of 90 pieces of data. This is a fairly small population but it was the only set easily available. From the 90 I will randomly sample 50 pieces to investigate. The way I randomly sampled the population, was to number each set one to ninety (1-90), while also numbering ninety pieces of paper. I placed those pieces of data
Data handling - Hypotheses- Is there any correlation between the children's favourite sport and favourite subject in yr 8.?
Data handling coursework task Hypotheses > Is there any correlation between the children's favourite sport and favourite subject in yr 8.? > Do older people have a higher IQ than younger? > Do girls have a higher IQ than boys? > What is the most popular subject in yr 7? > Are girls smaller than boys? Q. Is there any correlation between the children's favourite sport and favourite subject in yr 8.? Result: I found out that I cannot do this hypotheses because it doesn't have any Quantitive data the data is all Qualitative. Do girls have a higher IQ than boys? The graph I am going to use to show this piece of data is the frequency polygon. In order to do this I will need to construct 2 tally charts to represent boys and girls. To Boys Girls Here is my graph Result: from the graph I can conclude that the boys and girls have the same IQ so the group is average. Q. What is the most popular subject in yr 7? Here is a tally chart to show the frequency and angle of the different subjects. The chart I am going to use is a pie chart Here is a pie chart to show my results. Result; from this graph it shows clearly that P.E is the most popular subject in yr7 > Do girls have a higher IQ than boys? To show this data I used random sampling to get 30 numbers when I did this I then used excel to locate yr 10 and 11 pupils from this data I used the sort function and put