Estimating the length of a line and the size of an angle.
Introduction This coursework is about estimating the length of a line and the size of an angle. The purpose of this is so that I could see which year group is better at estimating year 10 or year 11. The factors, which may influence people's estimations are the following, firstly age. Year 11 students are one year older than year ten students so it is likely that year 11 students will know more about estimation than year 10. Secondly skills may effect people's estimation because some people may have weak numerical skills while others may have good numerical skills. Thirdly the strategy of estimating can affect pupil's estimation because different strategies of estimating can influence different estimations. Furthermore experience can affect people's estimation because some people may already have done work on estimation and know a bit about it while others may have not. Plus education can affect people's answers because some people may have started education at an earlier age than others so they will have more knowledge than the people who started education late so it can affect people's estimations. Knowledge can cause variation in answers because some people may have more knowledge than others so they will no more and will able to estimate better than the others. In addition background can cause variation of peoples estimations because some people may have come from LEDC
Statistics Coursework
STATISTICS COURSEWORK Tesheen Moosa Statistics Coursework Introduction I have been asked to examine the student's attendance figures from all year groups (7, 8, 9, 10 and 11) at Hamilton Community College. I will be investigating whether the age of the students affects their attendance figures at school and does it affect their learning and exam results as well? To start my research, I was given the attendance figures by the school for all of the year groups for the 2003 - 2004 academic years. I will then start to process data (attendance figures) firstly by reducing the amount of data that I will have to process using the method of stratified sampling. By using stratified sampling I will then only use a fair amount of data according to the percentage that I'm comfortable with. I will only be using 20% of the attendance figures from each year. A scientific calculator is used, to randomly select attendance figures that I am going to use, so that the new set of statistics isn't bias and isn't affected by my conscious decision. Using the new set of data, I will collate the data in frequency tables (to display all of the frequency distributions), in order to enable easy interpretation and analysis. Secondly, after collating the data, I will then display the new set of data in forms of graphs/diagrams and charts so that it will be easier for me to compare and study the
Investigating the different relationships between the T-total and T-number of the T-shape by translating it to other positions on the grid.
Investigating the different relationships between the T-total and T-number of the T-shape by translating it to other positions on the
"The lengths of lines are easier to guess than angles. Also, that year 11's will be more accurate at estimating."
In this investigation, 3 year groups - years 9, 10 and 11, were asked to estimate the lengths of some lines and angles, and the results that the pupils produced are going to be analysed to try and prove or disprove the hypothesis of: "The lengths of lines are easier to guess than angles. Also, that year 11's will be more accurate at estimating." The reasons I think these things are because people are more used to seeing lines than they are angles, so this could mean that they are better at estimating the length of lines. The reason I think they year 11's will be more accurate is because they have done maths longer than the year 9's, so they have had more experience. I will be using an example of one line, and one angle, and the results of Year 9 and Year 11 estimates. This is secondary data which has been previously recorded, during a survey to find out the estimates that the pupils gave. This data is continuous as it is As there are 117 year 9's and 145 year 11's I will have to reduce the size of my sample as these numbers are too large to handle, so I will be using a stratified method to reduce the size of the samples as this method keeps the results for the year groups in proportion to each other. I am going to be sampling 60 people in total, out of the year 9's and year 11's, as this is a manageable amount, and it can represent the data from the two year groups
I want to find out if there is a connection between people's IQ and their average KS2 SATs results.
Maths Statistics Coursework Aim: I want to find out if there is a connection between people's IQ and their average KS2 SATs results. I have gotten my data from the internet and I will take what I need to use in my coursework. Hypothesis 1: I predict that the higher someone's IQ is, the higher their average KS2 SATs results will be. Plan and Analysis: I found a sheet of data put onto Microsoft Excel on the internet for a fictional school called Mayfield High School. Even though the school is made up, the data is based on real people and there are 1183 students in all. The data is details of male and Female students in years 7 to 11 e.g. Height, Weight or favourite colour. This data is a secondary piece of data, I had not collected the information myself, and it was already on and Excel worksheet ready for me. Also the data for each individual student that I have is mixed, some information is discrete (favourite TV program or IQ), but some pieces of information are continuous (height or weight). I had decided to see the connection between students IQ and her average KS2 SATs results. To do this I had to take a sample of students out of all the data that I had, for I could not sample the whole population, as there are too many students. I decided that a sample of 50 students was big enough to get a decent and fairly accurate result, but small enough not give me too much
find out if there is a connection between people's IQ and their average KS2 SATs results.
Maths Statistics Coursework Aim: I want to find out if there is a connection between people's IQ and their average KS2 SATs results. I have gotten my data from the internet and I will take what I need to use in my coursework. Hypothesis 1: I predict that the higher someone's IQ is, the higher their average KS2 SATs results will be. Plan and Analysis: I found a sheet of data put onto Microsoft Excel on the internet for a fictional school called Mayfield High School. Even though the school is made up, the data is based on real people and there are 1183 students in all. The data is details of male and Female students in years 7 to 11 e.g. Height, Weight or favourite colour. This data is a secondary piece of data, I had not collected the information myself, and it was already on and Excel worksheet ready for me. Also the data for each individual student that I have is mixed, some information is discrete (favourite TV program or IQ), but some pieces of information are continuous (height or weight). I had decided to see the connection between students IQ and her average KS2 SATs results. To do this I had to take a sample of students out of all the data that I had, for I could not sample the whole population, as there are too many students. I decided that a sample of 50 students was big enough to get a decent and fairly accurate result, but small enough not give me too much
Differences in wealth and life expectancy of the countries of the world
Maths Coursework Introduction For my mathematics coursework I have been given the task of finding the differences in wealth and life expectancy of the countries of the world. To my aide I shall have the World Factbook Data which was given to me by my maths teacher. The World Factbook Data contains the Gross Domestic Product (GDP) per capita; this is the economic value of all the goods and services produced by an economy over a specified period. It includes consumption, government purchases, investments, and exports minus imports. This is probably the best indicator of the economic health of a country. It is usually measured annually. Another thing the data contains is the Life expectancy at birth. Life expectancy is called the average life span or mean life span, in this case of the countries or continents. This informs me of the average age a person in the specified country is likely to like to. Using this data I shall try to prove hypotheses that I shall personally predict before carrying out the investigation. For my investigation I shall be using varieties of different ways to presenting my data and results. I shall use graphs, charts as well as tables to make the data easier to read and understand for the reader. This would enable me also to keep organised and follow what I have to do. To develop my work I shall use very reliable as well as advanced methods to
Analyse a set of results and investigate the provided hypothesise.
Introduction My name is Khalil Sayed-Hossen, I'm a year10 student and am carrying out the "Guesstimate" coursework task. For this coursework I am going to analyse a set of results and investigate the provided hypothesise. Plan Within the duration of producing this (Guestimate) coursework, I will first investigate the hypothesis given, that people estimate the length of lines better than the size of angles. Once I have done this I will begin to investigate hypothesise of my own. I will need to find away of proving and disproving these hypothesise through analysing relevant data. The data I will be using is from a pooled set of results that members of my class have collected and combined together to form a broad, clearer set of results. To be able to compare a set of results there must be a clear comparison. Since the results of the length of the line were given in the mm and the size of the angle in ° (degrees) there is no clear comparison. To be able to compare these two different types of data I will need to calculate the percentage error for each result. This is done by first calculating the differences between the actual size of the angle and the length of the line, i.e. errors, and then by using the formula: - Error ÷ Correct × 100 = percentage error Ways in which I can compare this data include, looking at the mean of the results, standard deviation and through
Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common.
Individual Study. Development of Quantitative and Qualitative measures of Human Impact on Wimbledon Common. Abstract A vegetation analysis has been performed at four sites on Wimbledon Common SW19 London, to assess the suitability of quantitative methods for determining human impact on the succession climax. Systematic stratified sampling based on the method of Querouille (1949) has been used Based on 25 sample points per site. A test of Yoda's law; C=W? -3/2 has been performed on tree stands, where ? = density of a stand, C= dry weight of matter and w is a constant, by using a correlation test. Log (combined diameters) as the dependent variable (y) and log (distance between pairs) as the independent (x) variable. Three out of four sites gave high values of r, indicating that Yoda's law may operate on the sample sites. This is thought to reflect human management of the common over 200 years as well as the mechanism of self-thinning. Using the point quadrat method (Curtis 1949) estimates of density d were obtained as: d= 1 / l 2 where l = ? li / n , where n = sample no and l i the determined lengths from the sample points. This showed discrimination between open and closed sites. A frequency analysis was carried out on this data to find the relative dominance of species X as: Relative dominance of species x= sum of circumferences for that species/ sum of
Used Cars - What main factor that affects the price of a second hand car
Aim To investigate what is the main factor that affects the price of a second car. Hypothesis A number of factors such as age, mileage and engine size all affect the second hand price of car but the factor that I feel affects the price most is mileage the car has done. I believe this to be true because as a car travels more and more miles the engine and the other parts of the car have lot of strain put on them and so begin to wear, which then makes the car less and less reliable. Therefore this is apparent in the second price of the car. The price spread of the small sized cars will be the smallest. This is because the engine size range of the car small sized cars is quite small and as the small sized cars to not depreciate fast. The large sized car will have the largest price spread, as the engine size range is the biggest and also because luxury cars that are quite expensive tend to have large engines sizes. That is why the price of the large sized cars will be greatest. Small sized cars depreciate a lot slower in price than large engine sized cars. I believe this because small sized cars have a fairly low price any way and so the price of those cars won't drop as dramatically as others. Also small sized cars have a bigger demand than large cars as large cars are more expensive to maintain and run. Introduction In this investigation I will collect information on a