DOCSLIB.ORG

Patterns in Decimals

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Patterns in Decimals Patterns in Decimals You encounter decimals every day. Prices displayed in stores and adver- tisements, statistics in the sports section of the newspaper, and call num- bers on books in the library are often given as decimals. In this lesson, you will review the meaning of decimals, and you will practice working with decimals in a variety of situations. MATERIALS Explore • Spare Change cards (1 set per Read the rules of the Spare Change game, and then play two rounds group) with your group. • dollar charts Spare Change Game Rules (1 per player) •Place four Spare Change cards face up on the table. Place the rest of the deck face down in a pile. •To take a turn, a player chooses one of the four cards showing and shades that fraction of a dollar on his or her dollar chart. The player then places the card on the bottom of the deck, and replaces it with the top card from the deck. ① Possible answer: Ialways chose the greatest value I could, or I would try to choose a value that would not allow my opponent to get $1.00 perfectly. When I was closer to a dollar than •Play continues until one player has shaded the entire card or is my partner, I could unable to shade any of the four amounts showing. sometimes choose a •The player who has shaded the amount closest to a dollar at the card so that all the remaining cards would end of the game is the winner. put my partner over a dollar. Describe some strategies you used while playing the game. See ①. ② Possible answer: ② I learned to look Discuss what you learned about decimals. See . carefully at the decimal places—$.5 is 50 cents, not 5 cents! 112 CHAPTER 2 All about Numbers Investigation 1 Understanding Decimals Decimals are equivalent to fractions whose denominators are 10, 100, 1,000, 10,000, and so on. Each decimal place has a name based on the fraction it represents. Just Decimal Equivalent Fraction In Words the 0.1 ᎏ1ᎏ one tenth facts 10 ᎏ1ᎏ The prefix “deci” comes 0.01 100 one hundredth from the Latin word 1 0.001 ᎏᎏ one thousandth decem, meaning “ten.” 1,000 ᎏ1ᎏ 0.0001 10,000 one ten-thousandth EXAMPLE How is 9.057 different from 9.57? These decimals look similar, but they represent different numbers. You can see this by looking at the place values of the digits. 9 . 057 9 . 57 ϩ ᎏ0ᎏ ϩ ᎏ5ᎏ ϩ ᎏ7ᎏ ᎏ5ᎏ7 ᎏ9,0ᎏ57 9.057 means 9 10 100 1,000,or 91,000, or 1,000. ϩ ᎏ5ᎏ ϩ ᎏ7ᎏ ᎏ5ᎏ7 ᎏ95ᎏ7 9.57 means 9 10 100,or 9100, or 100. The number 9.057 is read “nine and fifty-seven thousandths.” The number 9.57 is read “nine and fifty-seven hundredths.” In Problem Set A, you will see how the ideas discussed above relate to the Spare Change game. LESSON 2.3 Patterns in Decimals 113 MATERIALS Problem Set A dollar charts 1. Consider the values $.3 and $.03. a. Are these values the same? no ϭ ᎏ3ᎏ 1b. $.3 10 dollar, b. Explain your answer to Part a by writing both amounts as fractions. ϭ ᎏ3ᎏ $.03 100 dollar c. Illustrate your answer to Part a by shading both amounts on a dollar chart. See below. 2. Do $.3 and $.30 represent the same value? Explain your answer by writing both amounts as fractions and by shading both amounts on a dollar chart. See below. Just 3. In her first four turns of the Spare Change game, Rosita chose $.45, $.1, $.33, and $.05. the facts a. Complete a dollar chart showing the amount Rosita should have In many countries, a shaded after the first four turns. See below. decimal comma is used instead of a decimal b. What part of a dollar is shaded on Rosita’s chart? Express your answer as a fraction and as a decimal. ᎏ9ᎏ3 point, and a space is 100, 0.93 used to separate c. How much more does Rosita need to have $1.00? Express your groups of three digits. ᎏ7ᎏ answer as a decimal and as a fraction. 100 dollar, $.07 4. Shade 12 whole 4. How could you shade a dollar chart to represent $.125? ᎏ1ᎏ rectangles and 2 of another. Now you will explore how multiplying or dividing a number by 10, 100, 1,000, and so on changes the position of the decimal point. 1c. Possible chart: ϭ ᎏ3ᎏ 2. yes; $.3 10 dollar, ϭ ᎏ3ᎏ0 ϭ ᎏ3ᎏ $.30 100 dollar 10 dollar Possible chart: 3a. 114 CHAPTER 2 All about Numbers Problem Set B 1. Copy this table: Calculation Result ؒ ϭ Just 81.07 81.07 1 81.07 ϭ 81.07 ؒ 10 810.7 10 ؒ 81.07 the facts 81.07 ؒ 10 ؒ 10 ϭ 81.07 ؒ 100 8,107 The numbers 10, 100, 81.07 ؒ 10 ؒ 10 ؒ 10 ϭ 81.07 ؒ 1,000 81,070 and so 81.07 ؒ 10 ؒ 10 ؒ 10 ؒ 10 ϭ 81.07 ؒ 10,000 810,700 ,10,000 ,1,000 ؒ on are called powers of ؒ ؒ ؒ ؒ ؒ ϭ ten because they can 81.07 10 10 10 10 10 81.07 100,000 8,107,000 be written as 10 raised to a power. For example: a. Enter the number 81.07 on your calculator. Multiply it by 10, and record the result in the second row of the table. •10 ϭ 101 ؒ • 1,000 ϭ 103 b. Find 81.07 100 by multiplying your result from Part a by 10. Record the result in the table. 2a. 78,010 ;c. Continue to multiply each result by 10 to find 81.07 ؒ 1,000 .2b. 0.3 81.07 ؒ 10,000; and 81.07 ؒ 100,000. Record your results 2c. 9,832,000 d. Describe how the position of the decimal point changed each time 2d. Possible answer: you multiplied by 10. It moved one place to the right. I moved the deci- mal point one 2. In Parts a–c, predict the value of each product without doing any place to the right calculations. Check your prediction by using your calculator. for each 0. a. 7.801 ؒ 10,000 b. 0.003 ؒ 100 c. 9,832 ؒ 1,000 3a. It is multiplied by 10. It is multiplied d. When you predicted the results of Parts a–c, how did you deter- by 100. It is multi- mine where to put the decimal point? plied by 1,000. 3. Think about how the value of a number changes as you move the 3b. Possible answer: decimal point to the right. The value of a. How does the value of a number change when you move the deci- the number is multiplied by 10 mal point one place to the right? Two places to the right? Three for each decimal places to the right? (Hint: Look at your completed table from place moved. Problem 1, or test a few numbers to see what happens.) 4a. 100; Possible b. Challenge In general, what is the relationship between the explanation: To get number of places a decimal is moved to the right and the change from 2.4 to 240, in the value of the number? the decimal point is moved two 4. Tell what number you must multiply the given number by to get places to the right. 240. Explain how you found your answer. 4b. 1,000; Possible a. 2.4 b. 0.24 c. 0.00024 explanation: To get from 0.24 to 240, 4c. 1,000,000; Possible explanation: the decimal point To get from 0.00024 to 240, the is moved three decimal point is moved six places places to the right. to the right. LESSON 2.3 Patterns in Decimals 115 Problem Set C 1. Copy this table: Calculation Result 81.07 81.07 Ϭ ϭ ᎏ1ᎏ 81.07 10 10 of 81.07 8.107 Ϭ Ϭ ϭ ᎏ1ᎏ 81.07 10 10 100 of 81.07 0.8107 81.07 Ϭ 10 Ϭ 10 Ϭ 10 ϭ ᎏ1ᎏ of 81.07 1d. It moved one place 1,000 0.08107 to the left. Ϭ Ϭ Ϭ Ϭ ϭ ᎏ1ᎏ 81.07 10 10 10 10 10,000 of 81.07 0.008107 2a. 0.001414 Ϭ Ϭ Ϭ Ϭ Ϭ ϭ ᎏ1ᎏ 81.07 10 10 10 10 10 100,000 of 81.07 0.0008107 2b. 343.72 ᎏ1ᎏ 2c. 0.877 a. Find 10 of 81.07 by entering 81.07 on your calculator and dividing by 10. Record the result in the second row of the table. 2d. Possible answer: I ᎏ1ᎏ moved the decimal b. Find 100 of 81.07 by dividing your result from Part a by 10. point one place to Record the result in the table. the left for each 0. ᎏ1ᎏ ᎏ1ᎏ c. Continue to divide each result by 10 to find 1,000 of 81.07; 10,000 3a. It is divided by 10. of 81.07; and ᎏ1ᎏ of 81.07. Record your results. It is divided by 100,000 100. It is divided d. Describe how the position of the decimal point changed each time ᎏ1ᎏ by 1,000. you divided by 10 (that is, each time you found 10). 3b. Possible answer: 2. In Parts a–c, predict each result without doing any calculations.
Load more

Recommended publications
  • EECE 1070 Curve Fitting and Data Analysis
    University of Massachusetts Lowell ECE EECE 1070 Introduction to Engineering for ECE Curve Fitting and Data Analysis using Matlab Objectives: To learn how to do linear and polynomial curve fitting. To learn Some basic data analysis techniques in Matlab; To learn to use graphical visualization techniques to understand system behavior. Part 1 Curvefitting: In the table below is the are the winning time, year, and name for the 100- meter dash. Year Winner and Country Time (secs) 1928 Betty Robinson, USA 12.2 1932 Stella Walsh, POL 11.9 1936 Helen Stephens, USA 11.5 1948 Fanny Blankers-Koen, NED 11.9 1952 Marjorie Jackson, AUS 11.5 1956 Betty Cuthbert, AUS 11.5 1964 Wyomia Tyus, USA 11.4 1968 Wyomia Tyus, USA 11.08 1972 Renate Stecher, E. Ger 11.07 1976 Annegret Richter, W. Ger 11.08 1980 Lyudmila Kondratyeva, USSR 11.06 1984 Evelyn Ashford, USA 10.97 1988 Florence Griffith Joyner, USA 10.54 1992 Gail Devers, USA 10.82 1996 Gail Devers, USA 10.94 2000 Marion Jones, USA 10.75 (a) Using Matlab, create two arrays one for the year and one for the times of the best finisher. Note that there is a steady decrease, albeit irregular decrease in the finishing time over the years 1928 to 2000. Plot year (x-axis) versus finishing time (y-axis). Include a title “Women’s 100-meter time versus year”, x-axis title (“year”) and y’axis title “finishing time (sec)” (b) Using the polyfit command, find a best first order least squares fit to the data by a line: Hint: Fit1=polyfit(year,finish,1).
    [Show full text]
  • The Olympic 100M Sprint
    Exploring the winning data: the Olympic 100 m sprint Performances in athletic events have steadily improved since the Olympics first started in 1896. Chemists have contributed to these improvements in a number of ways. For example, the design of improved materials for clothing and equipment; devising and monitoring the best methods for training for particular sports and gaining a better understanding of how energy is released from our food so ensure that athletes get the best diet. Figure 1 Image of a gold medallist in the Olympic 100 m sprint. Year Winner (Men) Time (s) Winner (Women) Time (s) 1896 Thomas Burke (USA) 12.0 1900 Francis Jarvis (USA) 11.0 1904 Archie Hahn (USA) 11.0 1906 Archie Hahn (USA) 11.2 1908 Reginald Walker (S Africa) 10.8 1912 Ralph Craig (USA) 10.8 1920 Charles Paddock (USA) 10.8 1924 Harold Abrahams (GB) 10.6 1928 Percy Williams (Canada) 10.8 Elizabeth Robinson (USA) 12.2 1932 Eddie Tolan (USA) 10.38 Stanislawa Walasiewick (POL) 11.9 1936 Jessie Owens (USA) 10.30 Helen Stephens (USA) 11.5 1948 Harrison Dillard (USA) 10.30 Fanny Blankers-Koen (NED) 11.9 1952 Lindy Remigino (USA) 10.78 Majorie Jackson (USA) 11.5 1956 Bobby Morrow (USA) 10.62 Betty Cuthbert (AUS) 11.4 1960 Armin Hary (FRG) 10.32 Wilma Rudolph (USA) 11.3 1964 Robert Hayes (USA) 10.06 Wyomia Tyus (USA) 11.2 1968 James Hines (USA) 9.95 Wyomia Tyus (USA) 11.08 1972 Valeriy Borzov (USSR) 10.14 Renate Stecher (GDR) 11.07 1976 Hasely Crawford (Trinidad) 10.06 Anneqret Richter (FRG) 11.01 1980 Allan Wells (GB) 10.25 Lyudmila Kondratyeva (USA) 11.06 1984 Carl Lewis (USA) 9.99 Evelyn Ashford (USA) 10.97 1988 Carl Lewis (USA) 9.92 Florence Griffith-Joyner (USA) 10.62 1992 Linford Christie (GB) 9.96 Gail Devers (USA) 10.82 1996 Donovan Bailey (Canada) 9.84 Gail Devers (USA) 10.94 2000 Maurice Green (USA) 9.87 Eksterine Thanou (GRE) 11.12 2004 Justin Gatlin (USA) 9.85 Yuliya Nesterenko (BLR) 10.93 2008 Usain Bolt (Jam) 9.69 Shelly-Ann Fraser (Jam) 10.78 2012 Usain Bolt (Jam) 9.63 Shelly-Ann Fraser (Jam) 10.75 Exploring the wining data: 100 m sprint| 11-16 Questions 1.
    [Show full text]
  • Womenʼs 100 Metres 51 Entrants
    IAAF World Championships • Biographical Entry List (may include reserves) Womenʼs 100 Metres 51 Entrants Starts Sunday, August 11 Age (Days) Born 2013 Best Personal Best 112 BREEN Melissa AUS 22y 326d 1990 11.25 -13 11.25 -13 Won sprint double at 2012 Australian Championships ... 200 pb: 23.12 -13. sf WJC 100 2008; 1 Pacific Schools Games 100 2008; 8 WSG 100 2009; 8 IAAF Continental Cup 100 2010; sf COM 100 2010; ht OLY 100 2012. 1 Australian 100/200 2012 (1 100 2010). Coach-Matt Beckenham In 2013: 1 Canberra 100/200; 1 Adelaide 100/200; 1 Sydney “Classic” 100/200; 3 Hiroshima 100; 3 Fukuroi 200; 7 Tokyo 100; 3ht Nivelles 100; 2 Oordegem Buyle 100 (3 200); 6 Naimette-Xhovémont 100; 6 Lucerne 100 ʻBʼ; 2 Belgian 100; 3 Ninove Rasschaert 200 129 ARMBRISTER Cache BAH 23y 317d 1989 11.35 11.35 -13 400 pb: 53.45 -11 (55.28 -13). 200 pb: 23.13 -08 (23.50 -13). 3 Central American & Caribbean Champs 4x100 2011. Student of Marketing at Auburn University In 2013: 1 Nassau 400 ʻBʼ; 6 Cayman Islands Invitational 200; 4 Kingston ”Jamaica All-Comers” 100; 1 Kingston 100 ʻBʼ (May 25); 1 Kingston 200 (4 100) (Jun 8); 2 Bahamian 100; 5 Central American & Caribbean Champs 100 (3 4x100) 137 FERGUSON Sheniqua BAH 23y 258d 1989 11.18 11.07 -12 2008 World Junior Champion at 200m ... led off Bahamas silver-winning sprint relay team at the 2009 World Championships 200 pb: 22.64 -12 (23.32 -13). sf World Youth 100 2005 (ht 200); 2 Central American & Caribbean junior 100 2006; 1 WJC 200 2008 (2006-8); qf OLY 200 2008; 2 WCH 4x100 2009 (sf 200, qf 100); sf WCH 200 2011; sf OLY 100 2012.
    [Show full text]
  • World Rankings — Women's
    World Rankings — Women’s 100 © GIANCARLO COLOMBO/PHOTO RUN The ’08 Olympic gold led to the first of Shelly-Ann Fraser- Pryce’s 5 No. 1s in a 12-year span 1956 1957 1 .................... Betty Cuthbert (Australia) 1 ...................Marlene Willard (Australia) 2 ........ Christa Stubnick (East Germany) 2 .................... Betty Cuthbert (Australia) 3 ...................Marlene Willard (Australia) 3 ...............Vera Krepkina (Soviet Union) 4 ..............Galina Popova (Soviet Union) 4 ...........Hannie Bloemhof (Netherlands) 5 .............................Isabelle Daniels (US) 5 ..... Gisela Birkemeyer (East Germany) 6 ...................... Giuseppina Leone (Italy) 6 ..............Galina Popova (Soviet Union) 7 ..... Gisela Birkemeyer (East Germany) 7 .......................... Erica Willis (Australia) 8 ......................June Paul (Great Britain) 8 .....Brunhilde Hendrix (West Germany) 9 ..............Heather Young (Great Britain) 9 .........................Fleur Mellor (Australia) 10 ..... Galina Rezchikova (Soviet Union) 10 ..........Madeleine Cobb (Great Britain) © Track & Field News 2020 — 1 — World Rankings — Women’s 100 1958 1962 1 ...................Marlene Willard (Australia) 1 ............ Dorothy Hyman (Great Britain) 2 .................... Betty Cuthbert (Australia) 2 ..............................Wilma Rudolph (US) 3 ...............................Barbara Jones (US) 3 ................ Jutta Heine (West Germany) 4 ..............Heather Young (Great Britain) 4 ..........................Teresa Ciepła (Poland) 5
    [Show full text]
  • 2014 European Championships Statistics – Women's 100M
    2014 European Championships Statistics – Women’s 100m by K Ken Nakamura All time performance list at the European Championships Performance Performer Time Wind Name Nat Pos Venue Year 1 1 10.73 2.0 Christine Arron FRA 1 Budapest 1998 2 10.81 1.3 Christine Arron 1sf1 Budapest 1998 3 2 10.83 2.0 Irina Privalova RUS 2 Budapest 1998 4 3 10.87 2.0 Ekaterini Thanou GRE 3 Budapest 1998 5 4 10.89 1.8 Katrin Krabbe GDR 1 Split 1990 6 5 10.91 0.8 Marlies Göhr GDR 1 Stuttgart 1986 7 10.92 0.9 Ekaterini Thanou 1sf2 Budapest 1998 7 6 10.92 2.0 Zhanna Pintusevich -Block UKR 4 Budapest 1998 9 10.98 1.2 Marlies Göhr 1sf2 Stuttgart 1986 10 11.00 1.3 Zhanna Pintusevich -Block 2sf1 Budapest 1998 11 11.01 -0.5 Marlies Göhr 1 Athinai 1982 11 11.01 0.9 Zhanna Pintusevich -Block 1h2 Helsinki 1994 13 11.02 0.6 Irina Privalova 1 Helsinki 1994 13 11.02 0.9 Irina Privalova 2sf2 Budapest 1998 15 7 11.04 0.8 Anelia Nuneva BUL 2 Stuttgart 1986 15 11.04 0.6 Ekaterini Thanou 1h4 Budapest 1998 17 8 11.05 1.2 Silke Gladisch -Möller GDR 2sf2 Stuttgart 1986 17 11.05 0.3 Ekaterini Thanou 1sf2 München 2002 19 11.06 -0.1 Marlies Göhr 1h2 Stuttgart 1986 19 11.06 -0.8 Zhanna Pintusevich -Block 1h1 Budapest 1998 19 9 11.06 1.8 Kim Gevaert BEL 1 Göteborg 2006 22 10 11.06 1.7 Ivet Lalova BUL 1h2 Helsinki 2012 22 11.07 0.0 Katrin Krabbe 1h1 Split 1990 22 11 11.07 2.0 Melanie Paschke GER 5 Budapest 1998 25 11.07 0.3 Ekaterini Thanou 1h4 München 2002 25 11.08 1.2 Anelia Nuneva 3sf2 Stuttga rt 1986 27 12 11.08 0.8 Nelli Cooman NED 3 Stuttgart 1986 28 11.09 0.8 Silke Gladisch -Möller
    [Show full text]
  • World Rankings — Women's
    World Rankings — Women’s 200 © VICTOR SAILER/PHOTO RUN Dafne Schippers & Elaine Thompson were the No. 1s of ’15 & ’16 1956 1957 1 .................... Betty Cuthbert (Australia) 1 ...................Marlene Willard (Australia) 2 ........ Christa Stubnick (East Germany) 2 .................... Betty Cuthbert (Australia) 3 ................... Maria Itkina (Soviet Union) 3 ..... Gisela Birkemeyer (East Germany) 4 ...................Marlene Willard (Australia) 4 ................... Maria Itkina (Soviet Union) 5 ......................June Paul (Great Britain) 5 ........................Nancy Boyle (Australia) 6 ..................... Norma Croker (Australia) 6 ........ Albina Kobranova (Soviet Union) 7 .....................Barbara Sobotta (Poland) 7 ...........Hannie Bloemhof (Netherlands) 8 ..... Gisela Birkemeyer (East Germany) 8 ..............Heather Young (Great Britain) 9 ..................Vera Yugova (Soviet Union) 9 .....................Barbara Sobotta (Poland) 10 ...............Jean Scriven (Great Britain) 10 ............Galina Popova (Soviet Union) © Track & Field News 2020 — 1 — World Rankings — Women’s 200 1958 1962 1 ...................Marlene Willard (Australia) 1 ................ Jutta Heine (West Germany) 2 .................... Betty Cuthbert (Australia) 2 ............ Dorothy Hyman (Great Britain) 3 ..............Heather Young (Great Britain) 3 .................................Vivian Brown (US) 4 ........ Christa Stubnick (East Germany) 4 .....................Barbara Sobotta (Poland) 5 ......................June Paul (Great Britain)
    [Show full text]
  • Guy Ginciene a Evolução Histórica Da Corrida De Velocidade
    UNIVERSIDADE ESTADUAL PAULISTA “JÚLIO DE MESQUITA FILHO” INSTITUTO DE BIOCIÊNCIAS - RIO CLARO BACHARELADO EM EDUCAÇÃO FÍSICA GUY GINCIENE A EVOLUÇÃO HISTÓRICA DA CORRIDA DE VELOCIDADE: UM APROFUNDAMENTO NA PROVA DOS 100 METROS RASOS Rio Claro 2009 GUY GINCIENE A EVOLUÇÃO HISTÓRICA DA CORRIDA DE VELOCIDADE: UM APROFUNDAMENTO NA PROVA DOS 100 METROS RASOS Orientadora: SARA QUENZER MATTHIESEN Trabalho de Conclusão de Curso apresentado ao Instituto de Biociências da Universidade Estadual Paulista “Júlio de Mesquita Filho” - Câmpus de Rio Claro, para obtenção do grau de Bacharel em Educação Física. UNESP – CAMPUS RIO CLARO 2009 796.4 Ginciene, Guy G492e A evolução histórica da corrida de velocidade : um aprofundamento na prova dos 100 metros rasos / Guy Ginciene. - Rio Claro : [s.n.], 2009 192 f. : il., figs., gráfs., quadros, fots. Trabalho de conclusão de curso (Bacharelado em Educação Física) - Universidade Estadual Paulista, Instituto de Biociências de Rio Claro Orientador: Sara Quenzer Matthiesen 1. Atletismo. 2. Atletismo - História. 3. 100 metros rasos. I. Título. Ficha Catalográfica elaborada pela STATI - Biblioteca da UNESP Campus de Rio Claro/SP Dedico esse trabalho aos meus ídolos/pais, Mauro e Clovet. AGRADECIMENTOS Gostaria de agradecer aos meus pais, por tudo que já fizeram por mim. Agradeço pela educação que me deram, e pelo grande exemplo que são para mim. Graças a eles, hoje estou terminado o curso de Educação Física em uma das melhores universidades do país. Mais do que isso, eles sempre me apoiaram na escolha desse curso que gosto tanto e tenho o prazer de estudar. Graças aos meus pais, tive a oportunidade de estudar em um excelente colégio, no qual, logo no meu primeiro ano, conheci o professor Márcio de Educação Física, que talvez nem se lembre mais de mim, mas que foi fundamental para que eu me apaixonasse pelo mundo da Educação Física.
    [Show full text]
  • Argento - Bronzo
    OLIMPIADI L'Albo d'Oro delle Olimpiadi Atletica Leggera DONNE 100 METRI ANNO ORO - ARGENTO - BRONZO 2016 E. Thompson (JAM) 10”71, T. Bowie (USA) 10”83, S. A. Fraser (JAM) 10,86 2012 Shelly-Ann Fraser (JAM), Carmelita Jeter (USA), Veronica Campbell (JAM) 2008 Shelly-Ann Fraser (JAM), Sherone Simpson (JAM), Kerron Stewart (JAM) 2004 Yuliva Nesterenko (BLR), Lauryn Williams (USA), Veronica Campbell (JAM) 2000 vacante, Ekaterini Thanou (GRE), Tanya Lawrence (JAM), Merlene Ottey-Page (JAM) (Marion Jones (USA) squal.doping, 2 argenti 1 bronzo) 1996 Gail Devers (USA), Merlene Ottey (JAM), Gwen Torrence (USA) 1992 Gail Devers (USA), Juliet Cuthbert (JAM), Irina Privalova (CSI) 1988 Florence Griffith-Joyner (USA), Evelyn Ashford (USA), Heike Drechsler (GEE) 1984 Evelyn Ashford (USA), Alice Brown (USA), Merlene Ottey-Page (JAM) 1980 Lyudmila Kondratyeva (URS), Marlies Göhr (GEE), Ingrid Lange-Auerswald (GEE) 1976 Annegret Richter (GEO), Renate Stecher (GEE), Inge Helten (GEO) 1972 Renate Stecher (GEE), Raelene Boyle (AUS), Silvia Chivás (CUB) 1968 Wyomia Tyus (USA), Barbara Ferrell (USA), Irena Szewinska (POL) 1964 Wyomia Tyus (USA), Edith McGuire (USA), Ewa Klobukowska (POL) 1960 Wilma Rudolph (USA), Dorothy Hyman (GBR), Giuseppina Leone (ITA) 1956 Betty Cuthbert (AUS), Christa Stubnick (GER), Marlene Matthews (AUS) 1952 Marjorie Jackson (AUS), Daphne Hasenjäger (SAF), Shirley Strickland-de la Hunty (AUS) 1948 Fanny Blankers-Koen (OLA), Dorothy Manley (GBR), Shirley Strickland-de la Hunty (AUS) 1936 Helen Stephens (USA), Stanislawa Walasiewicz (POL), Käthe Krauss (GER) 1932 Stanislawa Walasiewicz (POL), Hilda Strike (CAN), Wilhelmina Van Bremen (USA 1928 Elizabeth Robinson (USA), Fanny Rosenfeld (CAN), Ethel Smith (CAN) 1896-1924 Non in programma 200 METRI ANNO ORO - ARGENTO - BRONZO 2016 E.
    [Show full text]
  • Progression of the European Outdoor Records
    Progresión de los Récords de Europa al Aire Libre Progression of the European Outdoor Records (cerrado a / as at 31.10.2016) Revisado, completado, corregido y actualizado Revised, completed, corrected and updated Por/by José María García “A los admirados atletas europeos de todas las épocas y a Devoted to all the admired european athletes of all time, mis estimados colegas estadísticos, españoles y extranjeros, and to my respected colleagues in statistics, both spaniards con los que me he relacionado en el último medio siglo”. and foreign, whom I have met in the last half century. Introducción Introduction Permitidme unas breves líneas como introducción a la Allow me a few brief lines as an introduction to the list cronología de récords y mejores marcas de Europa que tengo of records and European best performances which I am ho- el honor de presentar. noured to present. En primer lugar tengo que manifestar algo obvio; se trata In the first place I have to state the obvious: it is a list de una lista de marcas con un breve suplemento, y no de un re- of performances with a brief supplement and not a story, nor lato -ni siquiera muy resumido- de la historia del atletismo eu- even a summary, of the history of European athletics (the Ita- ropeo (de ello ya se ocuparon en su día, con la debida lian experts Roberto Quercetani and Luciano Serra – and the extensión, entre otros, los expertos italianos Roberto Querce- Frenchman Gaston Meyer – among others in their day took tani y Luciano Serra- y el francés Gaston Meyer-, en los años care of that with due extent in the Sixties).
    [Show full text]
  • Young Investigator Research Article ANTHROPOMETRIC
    ©Journal of Sports Science and Medicine (2005) 4, 608-616 http://www.jssm.org Young investigator Research article ANTHROPOMETRIC COMPARISON OF WORLD-CLASS SPRINTERS AND NORMAL POPULATIONS Niels Uth Department of Sport Science, University of Aarhus, Aarhus N, Denmark Received: 30 May 2005 / Accepted: 25 August 2005 / Published (online): 01 December 2005 ABSTRACT The present study compared the anthropometry of sprinters and people belonging to the normal population. The height and body mass (BM) distribution of sprinters (42 men and 44 women) were statistically compared to the distributions of American and Danish normal populations. The main results showed that there was significantly less BM and height variability (measured as standard deviation) among male sprinters than among the normal male population (US and Danish), while female sprinters showed less BM variability than the US and Danish normal female populations. On average the American normal population was shorter than the sprinters. There was no height difference between the sprinters and the Danish normal population. All female groups had similar height variability. Both male and female sprinters had lower body mass index (BMI) than the normal populations. It is likely that there is no single optimal height for sprinters, but instead there is an optimum range that differs for males and females. This range in height appears to exclude people who are very tall or very short in stature. Sprinters are generally lighter in BM than normal populations. Also, the BM variation among sprinters is less than the variation among normal populations. These anthropometric characteristics typical of sprinters might be explained, in part, by the influence the anthropometric characteristics have on relative muscle strength and step length.
    [Show full text]
  • Where There's Life, There's Maths
    EXTENDED TASKS FOR GCSE MATHEMATICS A series of modules to support school-based assessment Where There's Life, There's Maths MIDLAND EXAMINING GROUP SHELL CENTRE FOR MATHEMATICAL EDUCATION 510.0171 MID EXTENDED TASKS FOR GCSE MATHEMATICS A series of modules to support school-based assessment Where There's Life, There's Maths MIDLAND EXAMINING GROUP SHELL CENTRE FOR MATHEMATICAL EDUCATION National STEM Centre N23921 Extended Tasks for GCSE Mathematics : Applications Authors This book is one of a series forming a support package for GCSE coursework in mathematics. It has been developed as part of a joint project by the Shell Centre for Mathematical Education and the Midland Examining Group. The books were written by Steve Maddern and Rita Crust working with the Shell Centre team, including Alan Bell, Barbara Binns, Hugh Burkhardt, Rosemary Eraser, John Gillespie, Richard Phillips, Malcolm Swan and Diana Wharmby. The project was directed by Hugh Burkhardt. A large number of teachers and their students have contributed to this work through a continuing process of trialling and observation in their classrooms. We are grateful to them all for their help and for their comments. Among the teachers to whom we are particularly indebted for their contributions at various stages of the project are Paul Davison, Ray Downes, John Edwards, Harry Gordon, Peter Jones, Sue Marshall, Glenda Taylor, Shirley Thompson and Trevor Williamson. The LEAs and schools in which these materials have been developed include Bradford: Bradford and Ilkley Community College;
    [Show full text]
  • Day by Day Notes for MATH 201 Spring 2014
    Day By Day Notes for MATH 201 Spring 2014 Day 1 Activity: Go over syllabus. Take roll. Overview example: Kristin Gilbert trial. Goals: Review course objectives: collect data, summarize information, and make inferences. I have divided this course into three “units”. Unit 1 (Days 2 through 14) is about summarizing data. Unit 2 (Days 15 through 29) is about sampling and probability. Unit 3 (Days 30 through 42) is about statistical inference. Throughout the course, we will also focus on the abuses people often make of statistics and statistical methods. Sometimes these abuses are unintentional. My hope is that at the end of the course, you will have an appreciation for the “tricks” that people use to lie to you using numbers. I use the Gilbert trial example because it demonstrates all three of the course’s main ideas in action. The charts we see are examples of how to organize and summarize information that may be complicated by several variables or dimensions (Unit 1). The argument about whether we would see results such as this one if there really were no relationship between the variables is an example of the probability we will study in Unit 2. And the trial strategy itself is what statistical inference is all about (Unit 3). Many of you will encounter inference when you read professional journals in your field and the researchers use statistics to support their conclusions of improved treatments or to estimate a particular proportion or average. I believe to be successful in this course you must READ the text carefully, working many practice problems.
    [Show full text]