Reaction Times

T His is the data I collected to prove my first hypothesis which was that I (and most people) work better at different times of day. I predicted that I would get my lowest reaction time during the afternoon because I believe that is the time when people are most alert and their reactions quickest. I also believe that the highest reaction times will be at night when people are feeling sleepy and will have slow reactions. Control: 0.35, 0.28, 1.03, 0.29, 0.22, 0.17, 0.2, 0.19, 0.2, 0.19, 0.16, 0.21, 0.23, 0.21, 0.18, 0.17, 0.16, 0.59, 1.16, 0.28, 0.18, 0.17, 0.18, 0.19, 0.18, 0.21, 0.18, 0.22, 0.2, 0.2, 0.45 I collected this at 17:02 because that was the time; I felt was when I was not too tired and not too awake! I decided that I would show the data I collected for the control first in a steam and leaf diagram and then present it in a line graph. Data collection This graph simply shows my control data- how ever I do not believe that this data is free from bias because it falls into the time frame for the evening so I could have just used this data for my experiment by using this as the results for the evening. So I don't think this is a very good control data but it will have to do because whatever time I choose to do results for the control, the control will be affected by that time of day. 7:00-12:00 0.21 0.43 0.26 0.24 0.38 0.03 0.34 0.1 0.22 0. 21 0.34 0.41 0.23

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  • Word count: 920
  • Level: GCSE
  • Subject: Maths
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Maths T-totals coursework

GCSE T-totals Coursework Introduction In this project I will be investigating the formula, patterns and relationships between the t-numbers, t-shape and t-totals in different sized grids 10x10, 9x9, 8x8, 7x7. I have a grid nine by nine starting with the numbers 1-54. There is a shape in the grid called the t-shape which is highlighted in red shown in the table below. 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 The t-number is the number at the bottom of the t-shape which is 20 The t-total is all the numbers in the t added up together which is 1+2+3+11+20=37 T-number T-total 20 37 21 42 22 47 23 52 24 57 25 62 26 67 As you can see: The t-number increases by 1 each time. The t-total increases by 5 each time is there a link? 20x5=100 00-63=37 the t-total The link between 63 and 9 is 7 because 7x9=63 So the formula is T-number x 5 (7x9) 5n -number-7x9 How did I work out this and what can we do with this formula? The formula starts with 5 as there is a rise between the t-total of 5 each time. We then -63. I got this number by working out the difference between the t-number and the other numbers in the t-shape. E.g. 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 20 21 22 23 24 25 26 27

  • Word count: 1547
  • Level: GCSE
  • Subject: Maths
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Gullivers theory - introduction

"... They measured my right thumb, and desired no more; for a mathematical computation that twice round my thumb is once round the wrist and so onto the neck and the waist..." (Extract from Gulliver's travels by Jonathan Swift) * Investigate using any valid statistical method. Aim The aim of the coursework is to prove whether or not Gulliver's theory is correct, (in accordance to the above extract), in reality. Hypothesis In my opinion, I do agree with the theory -to some extent- since, by measuring myself, I found the measurements of the body parts to be consistent with the other in agreement with the theory (± 4cm). However since I've tested it only on myself for now, I cannot apply this rule to everyone since there are many factors to be taken into account. And due to this fact, I believe that the theory is restricted to certain groups of people (e.g. those whose body parts are in direct proportion to the other) and may not necessarily comply with the majority as there are a number of aspects that can contribute to this. One factor which can alter the consistency of the theory is gender. Boys tend to have a larger body build than girls and hence, I do not believe the theory to be true in this case. And so for boys I would say that 'thrice round the thumb is once round the wrist, twice round the wrist is once round the neck and two and a half times round the

  • Word count: 1816
  • Level: GCSE
  • Subject: Maths
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Microsoft Excel Driving Tests Coursework

DRIVING TESTS INTRODUCTION I will investigate how well 240 people perform in their driving test. There is a mixture of male and female drivers and there are four instructors that teach them. I will investigate how many minor mistakes these driver's make in their test. The information I have been given consists of: * the driver's gender * the number of one hour lessons they have received * the number of minor mistakes made during the test * the instructor who gave the driver lessons * the day they took the test * the time of day that they took the test The software I will be using to store this information will be Microsoft Excel. I will house the information in spreadsheets and here I will be able to select random samples and sort my data. I will also be using a program called Autograph. This program will enable me to draw graphs and do important calculations. Without this software it would take me a long time to draw out the diagrams I need for the investigation. During the investigation I will be using sampling. This is where I will be taking a portion of the population to gather my results, instead of using all 240 people. This means that the data will be easier to handle and I will have less points to plot on my graphs but still keep accurate results. HYPOTHESIS ONE - MALES ARE BETTER DRIVERS THAN FEMALES For my first hypothesis I will be answering the

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  • Level: GCSE
  • Subject: Maths
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Statistics Project

Statistics Project Plan Aim My general aim from this investigation is to see if there is a relationship between the unemployment rate and the turnout of the 2005 general election in a random sample of different constituencies. Method I will randomly select 60 (about 10%) pieces of data as a sample by assigning each constituency a number and generating random numbers to choose the constituencies that are included in my sample. To make sure that my sample is as helpful as possible, it should be in the same proportion of winning parties to the actual thing, so the chosen constituencies were filtered so that each category had the right number of each party. I shall then plot the unemployment rate of these chosen constituencies against the turnout for that constituency in the 2005 general election in a graph, and note what I can discover from it and whether there is any correlation. If there is positive correlation I will know that places where more people are unemployed are likely to have a higher turnout for the general election, and if there is a negative correlation that it will seem the opposite. To carry out this investigation further, I plan to make two box and whisker plots to discover whether the constituencies who elect Labour are more likely to be unemployed. I will take a new random sample, taking 20 random constituencies from each of Labour and Conservative using

  • Word count: 1367
  • Level: GCSE
  • Subject: Maths
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Data handling - calculating means and standard deviations

ASSIGNMENT 1I Type I Name: Candidate #: [ ] School: October 2003 Question 1 The table below shows the height for 60 students in centimeters: Table 1 77 75 37 55 50 66 32 46 79 40 69 77 41 48 30 76 35 30 57 72 78 43 43 36 32 66 30 51 45 78 31 71 60 40 79 66 45 42 77 76 32 35 64 79 61 45 34 79 39 49 35 42 72 48 59 60 37 30 30 64 * The mean () is calculated using the equation below: = * The standard deviation () is calculated* using the equation below: = 17.08731661 Question 2 (a) The table below shows the height of 60 students after adding 5 cm to each height: Table 2 82 80 42 60 55 71 37 51 84 45 74 82 46 53 35 81 40 35 62 77 83 48 48 41 37 71 35 56 50 83 36 76 65 45 84 71 50 47 82 81 37 40 69 84 66 50 39 84 44 54 40 47 77 53 64 65 42 35 35 69 * The mean () is calculated using the equation below: = * The standard deviation () is calculated* using the equation below: = 17.08731661 (b) The table below shows the height of 60 students after subtracting 12 cm from each height: Table 3 65 63 25 43 38 54 20 34 67 28 57 65 29 36 18 64 23 18 45 60 66 31 31 24 20 54 18 39 33 66 19 59 48 28 67 54 33 30 65 64 20 23 52 67 49 33 22 67 27 37 23 30 60 36 47 48 25 18 18 52 *

  • Word count: 2086
  • Level: GCSE
  • Subject: Maths
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The decimal search

The Decimal Search method I would like to solve the equation x³ + 2x² - 0.5 = 0. Let f(x) = x³ + 2x² - 0.5 The graph below shows the equation y = x³ + 2x² - 0.5. As you can see, there are three roots/solutions when f(x) = 0. The equation x³ + 2x² - 0.5 = 0 cannot be solved algebraically so I will use the decimal search method. This method looks for a change in sign of the value of f(x). The following table gives values of x and f(x). x -2.0 -1.5 -1.0 -0.5 0 0.5 .0 .5 2.0 f(x) -0.5 0.625 0.5 -0.125 -0.5 0.125 2.5 7.375 5.5 As the curve crosses the x axis, the value of the function f(x) changes sign, for example: The values of f(x) in the table above confirms there are roots between [-2,-1.5] [-1,-0.5] and [0, 0.5]. I am going to concentrate on finding a more accurate value of the root between [-2,-1.5]. I will achieve this by reducing the size of the intervals to a width of 0.1. The graph and table below show that the root is between [-1.8,-1.9]. x -2.0 -1.9 -1.8 -1.7 -1.6 -1.5 f(x) -0.5 -0.139 0.148 0.367 0.524 0.625 By reducing the width of the interval even further, we can continue to find a more accurate interval. The interval is reduced to 0.01 and the root is between [-1.85,-1.86]. x -1.90 -1.89 -1.88 -1.87 -1.86 -1.85 -1.84 -1.83 -1.82 -1.81 -1.80 f(x) -0.1390 -0.1071 -0.0759 -0.0454 -0.0157 0.0134

  • Word count: 717
  • Level: GCSE
  • Subject: Maths
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Investigation into 100m times and long jump distances

Edexcel GCSE Statistics Coursework ictl Investigation into 100m times and long jump distances Introduction I intend to use my school’s athletic sports results database to conduct an investigation into the relationship between the 100m times and the long jump distances throughout the year groups. This database contains secondary data which are both quantitative and qualitative from years 7 to 11 in RGS. This data should be reliable because the data was recorded under supervision. I have chosen to use quantitative data for my investigation because qualitative data tends to be much more limited than quantitative data as quantitative data can take any numerical value whereas qualitative data can only take specific values (e.g. colours: blue, red green). I believe that the faster somebody runs the higher and further s/he will jump. I believe this because many fast runners have long legs, which enable them to run with a longer stride. Also, it takes more energy fore someone with shorter legs to run the same distance and at the same speed as somebody with longer legs. I also believe that somebody’s running speed will improve as he/she ages throughout secondary school. I believe this because many people start their growth spurt between year 8 and year 10 and will continue growing until they are about 18. Also, older people will improve as they grow older as

  • Word count: 2849
  • Level: GCSE
  • Subject: Maths
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Maths Statistics Coursework

Maths Statistics Coursework Guesstimate INTRODUCTION The title of my investigation is 'Guesstimate', as I will be looking at how accurate different people are at estimating. The aim of the investigation is to deduce estimating skills of pupils of different ages, abilities and genders. To do this I have created the following hypotheses: ) The older you are, the better you are at estimating. 2) The higher the band you are in, the better you are at estimating. 3) Boys are better than estimating than girls. In order to do this I will need to collect information for Key Stage 3, Key Stage 4 and Key Stage 5, and within the stages ability (band) and gender. I will collect this information from a database, which gives us: Key Stage, maths ability (higher, middle or lower band), gender and their estimates of an acute (17°), obtuse (147°) and reflex (302°) angle. However, I will only be using the information for the obtuse angle, because the acute would be extremely small so people may guess zero, which would affect our results. Also, reflex angles could be mistaken for acute angles and vice versa, so people may not be giving an accurate estimate. I will assume that the data is reliable, as I will eliminate bias from my sample by looking at the errors in guessing. To calculate percentage error I will use: This will make it easier to see how far out the pupils were from

  • Word count: 3495
  • Level: GCSE
  • Subject: Maths
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statistics coursework

Introduction Investigation between key stage 2 results and IQ I will investigate if higher Key Stage 2 has an affect on IQ. I am going to collect IQ and Key Stage 2 Maths Results randomly. I am going to get the data for this investigation from the Mayfield High School folder. I choose this source of information because reliable as it is the only data the school gave me, it was easy to get and it is easy to use. Any data that is missing or anomalous I will delete. I will use a total sample size of 30 if there are not enough results I will use all of them. I will use this data to establish if there is a relation ship between IQ and Key Stage 2 Result The calculations I will use in this Coursework are Inter-quartile range Upper-quartile Cumulative frequency Lower-quartile Frequency Median Averages Box plots These calculations will help me in the following ways: Average will help me by singling one data from a whole bunch to make it easier to compare. The frequency shows how often certain data occurs. The inter-quartile range will help me in a similar way. Box helps explain data visually. Cumulative frequency will show in tables and in graphs. samples Level 2 Level 3 Level 4 Level 5 Level 6 IQ IQ IQ IQ IQ 68 78 90 00 07 2 69 85 91 03 08 3 69 87 94 03 08 4 71 88 97 04 10 5

  • Word count: 1172
  • Level: GCSE
  • Subject: Maths
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