• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month
Page
  1. 1
    1
  2. 2
    2
  3. 3
    3
  4. 4
    4
  5. 5
    5
  6. 6
    6
  7. 7
    7
  8. 8
    8
  9. 9
    9
  10. 10
    10
  11. 11
    11
  12. 12
    12
  13. 13
    13
  14. 14
    14
  15. 15
    15
  16. 16
    16
  17. 17
    17
  18. 18
    18
  19. 19
    19
  20. 20
    20
  21. 21
    21
  22. 22
    22
  23. 23
    23
  24. 24
    24
  25. 25
    25
  • Level: GCSE
  • Subject: Maths
  • Word count: 3750

Maths Coursework. Statistics

Extracts from this document...

Introduction

Introduction Aim: To express evidence to support my hypothesis. Proving my hypothesis I will use: > scatter diagram > bar charts > tables > frequency table What I will do: > stratified sample > random sample > standard deviation > Find the mean, mode, median to compare my first hypothesis. To do these I will use a scientific calculator Introduction: Using the information given before me I have decided with three hypotheses that I shall investigate. These are: 1. Females longer than males. 2. The richer the country the higher the average birth rate. 3. The higher the continents GDP-per capita (in my data) the greater it's highest average age. For me to prove these hypotheses I will need to collect a sample of male ad females ages in addition to that I will also need to get a sample of money to do my second hypothesis, which is to compare both together. For this to be more accurate and for me to get enough information to compare I will need a big sample of countries, so I have chosen a sample of 50. to get my data for my hypotheses I used a scientific calculator to do a stratified sample and a random sample did a stratifies sample because it would tell me how many countries I should use from each continent (it would give me the same percentage for each continent as they all have different amount of counties.) the formula that I used on the calculator to get this information was: Country = how many continents in the country � how much I need . The number of continents in the world Asia = 54/235 �50 = 11.4893617 (12 rounded up) Africa = 57/235 �50 = 12.12765957 (12) Europe = 48/235 �50 =10.21276596 (10) Oceania = 25/235 �50 = 5.319148936 (5) North America = 37/235 �50 = 7.872340426 (8) South America = 14/235 �50 = 2.978723404 (3) ...read more.

Middle

Lowest average age: 50.52 (51) Life expectancy (years) Frequency (f) Mid-point (x) (fx) Fx2 Frequency density 35 � 45 0 40 0 0 0 45 � 55 1 50 50 2500 0.1 55 � 65 2 60 120 7200 0.2 65 � 75 5 70 350 24,500 0.5 Total: 8 520 34,200 Mean: ?fx =520/8=65 ? f Mode: 65 � 75 Median: 65 � 75 Standard deviation: 7.07 (2 d.p.) North America female Highest average age: 82.45(83) Lowest average age: 53.12(53) Life expectancy (years) Frequency (f) Mid-point (x) (fx) Fx2 Frequency density 35 � 45 0 40 0 0 0 45 � 55 1 50 50 2500 0.1 55 � 65 0 60 60 0 0 65 � 75 7 70 490 34,300 0.7 Total: 8 600 36,800 Mean: ?fx =600/8=75 ? f Mode: 65 � 75 Median: 65 � 75 Standard deviation: 3.20 (2.d.p.) Europe male Highest average age: 78.12(78) Lowest average age: 60.88(61) Life expectancy (years) Frequency (f) Mid-point (x) (fx) Fx2 Frequency density 35 � 45 0 40 0 0 0 45 � 55 0 50 0 0 0 55 � 65 1 60 60 3600 0.1 65 � 75 9 70 630 44,100 0.9 Total: 10 690 47,700 Mean: ?fx = 690/10= 69 ? f Mode: 65 � 75 Median: 65 � 75 Standard deviation: 3 Europe female Highest average age: 85.34(85) Lowest average age: 69.39(69) Life expectancy (years) Frequency (f) Mid-point (x) (fx) Fx2 Frequency density 35 � 45 0 40 0 0 0 45 � 55 0 50 0 0 0 55 � 65 0 60 0 0 0 65 � 75 10 70 700 49,000 1 Total: 10 700 49,000 Mean: ?fx = 700/10 = 70 ? f Mode: 65 < x ? 75 Median: 65 � 75 Standard deviation: 0 I have noticed that when I did the mode and median they are mostly the same for both male and female. ...read more.

Conclusion

I have also shown as my second hypothesis that 'the higher the G.D.P the longer the life expectancy.' I have shown this with three different sets of data, one for males, one for females and the other one for the G.D.P. I have done different graphs to compare the data and get an actual result to prove that my hypothesis is correct. I have also put a table to show my actual data that I had used to develop the graphs. I have highlighted the countries on the tables to show, which countries data did not confirm my hypothesis. I have done this for each continent to show the differences. I have also done each continent so I could get a more varied result to actually see if my hypothesis is true on all the continents. By doing this I have found out that not all the countries in different continents have a high G.D.P and a longer life expectancy. Finally for my third hypothesis I have shown that the higher the continents GDP-per capita (in my data) the greater it's highest average age. I used a table to compare the data to get the result that my hypothesis was correct. Overall I thought that the amount of data I used was enough to clearly interpret my data and come out with a final conclusion, which was that in most countries females live longer than males and also that the G.D.P had no effect on the age because in some countries the G.D.P was low and the age was high or in some it was that the G.D.P was high and the age was low. For example in Swaziland the G.D.P was high and the average life expectancy was low and also in Somalia the G.D.P was low and the average life expectancy was high. From my third hypothesis I found out that the higher the total amount of money in the whole continent the higher the average life expectancy. ...read more.

The above preview is unformatted text

This student written piece of work is one of many that can be found in our GCSE Height and Weight of Pupils and other Mayfield High School investigations section.

Found what you're looking for?

  • Start learning 29% faster today
  • 150,000+ documents available
  • Just £6.99 a month

Not the one? Search for your essay title...
  • Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

See related essaysSee related essays

Related GCSE Height and Weight of Pupils and other Mayfield High School investigations essays

  1. mayfield high statistics coursework

    Male Stratified Sample Results Year Group Surname Forename Height (m) Weight (kg) 7 Austin Steven 1.54 43 7 Lloyd Mark 1.61 56 7 Mills Robert 1.63 50 7 Pearce Stuart 1.50 34 7 Thorpe Billy 1.53 40 8 Freeman Ian 1.82 64 8 Jones Kevin 1.62 49 8 McGrail Craig

  2. A hypothesis is the outline of the idea/ideas which I will be testing and ...

    GIRLS HEIGHT GIRLS Height (cm) Cumulative Frequency Less than 140 0 Less than 150 5 Less than 160 16 Less than 170 17 Less than 180 20 Less than 190 20 Cumulative Frequency Diagram GIRLS Weight (kg) Cumulative Frequency Less than 40 5 Less than 50 13 Less than 60

  1. Edexcel GCSE Statistics Coursework

    than females will be greater; this can be proven by looking at the tallest of each sex. The tallest male is 1.83M and the tallest female is 1.72M, demonstrating the fact that males do eventually grow taller than females. This, despite it being on a small scale, can show us

  2. GCSE Maths Statistics Coursework

    To find out where to put my line of best fit I had to work out the mean of IQ and the Average SAT's Result, to work out the mean I had to add up all the figures in the IQ column and then divide it by forty, and to

  1. Mayfield High Statistics Coursework

    Male 100 5 8 Male 100 3 8 Male 103 4 8 Male 103 2 8 Male 104 3 8 Male 105 5 8 Male 107 5 8 Male 110 5 8 Male 117 5 8 Male 126 6 8 Male 127 6 9 Female 88 3 9 Female 88

  2. Statistics coursework - hypotheses based on students statistics

    IIII I 5 170-174 II 2 175-179 III 3 180-184 II 2 Now that I have got my data I can put it into the form of a bar graph. This has been done below. There are two bars alongside each other because then I can compare the two results against each other straight away.

  1. Mayfield maths courswork - is there a link between abilty in maths and abilty ...

    powerful as it is independent of sample size and the scales of measurement used. I will now calculate a separate product-moment correlation coefficient for the males and for the females to indeed confirm that the link between ability in Science and in Maths is greater for the male students than the female students.

  2. GCSE maths statistics coursework

    There are 604 boys and 579 girls in Mayfield High School. I am going to take a sample of 5% of boys and girls which is 30 boys and 29 girls. I will take the samples by pressing the random button on the calculator and then I will times it by 604 for boys and 579 for girls.

  • Over 160,000 pieces
    of student written work
  • Annotated by
    experienced teachers
  • Ideas and feedback to
    improve your own work