Data Visualisation

Question: Describe about the Data Visualisation? Answer: Introduction Data visualisation and analysis plays an important role in the business analytics. It provides various estimates for the future planning and strategy of business or industry. Data analysis has the key role in the managerial decision making. We have to analyse the data of marathon winner players and some related variables. For analysis of this data, we have to use different statistical methods and graphs for explaining in detail. Data is provided within the excel sheet. We have to visualise and analyse given data for more study. Let us see this data visualisation and analysis in detail. Data Elements We consider the following seven variables for the study of data analysis of Marathon winner players. The list of these variables is given below: No. Variable 1 Winner Name 2 Country 3 Category 4 Number of Wins 5 Date of birth 6 Year of first major marathon win 7 Age of first major marathon victory Data Visualisation and data analysis: In this part, we have to visualise and analyse the data given for the Marathon winner players. Also we have to see some statistical analysis for this data. We are given a data of 290 marathon winner players from different countries. Most of the marathon winner players are from United States. There are 63 marathon winner players are from United States. Second most marathon players are from the country Kenya. Out of 290 marathon players, 106 are female winner and 184 are male winner. Percentage for female marathon winner player is 36.6% and for male marathon winner player is 63.4%. Out of 290 marathon winner players, 194 players win the marathon only one time while only one player wins the marathon 11 times. Out of 290 marathon winners players, 28 players win the marathon at the age of 25 years. The variable age at first win follows an approximate normal distribution. The histogram associated with the age at first win clearly implies the approximate normal distribution. The average age at first victory is observed as 28.22 years with the standard deviation of 4.2 years. Cross tabulation for the country versus gender of the marathon winners players shows that ratio of the male and female marathon winner players is not same. The one sample t test implies that the average age of the marathon winner player at first win is 28 years. From the above scatter diagram, we conclude that there is no any linear relationship exists between number of wins and age at first victory. The correlation coefficient between these two variables is given as -0.11. Interpretations or conclusions: There is total number of observations for each variable is given as 290 and some observations for some variables are missing. There are maximum of 63 marathon winner players are of the country United States. There are 106 female winners given in the data and percentage of female is given as 36.6 out of total marathon winner players. Most of the players wins marathon only one time. Only one player wins marathon 11 times. The variable age at first win follows an approximately normal distribution. Average number of wins is given as 1.7 years and average age at first victory is given as 28.22 years. We conclude that there is no any linear relationship exists between the variables number of wins and age at first victory. This means that age factor is not important for first victory. References: Abramowitz, M., and Stegun, I.A., "Handbook of mathematical functions", Dover publications, New York, 1964 (1972) Crow, E.L., Davis, F.A., and Maxfield, M.W. "Statistics Manual", Dover publications, Inc New York, 1960 Fraser, D.A.S., "Nonparametric methods in statistics", John WileySons, New York, ChapmanHall, London, 1957 (2nd 1959) Kanji, G.K., "100 statistical tests", Sage publications London, Newbury Park, New Dehli, ISBN: 0 8039 8704 8, 1993 Papoulis, Athanasios "Probability and Statistics" Prentence-Hall International Editions, ISBN: 0 13 711730 2, 1990 Siegel, S. "Non-parametric statistics for the behavioral sciences", McGraw-Hill book company, Inc. New York, Toronto, London, 1956 Van den Brink, W.P., and Koele, P. "Statistiek, Deel 3: Toepassingen", Boom Meppel Amsterdam Rowntree, Statistics without tears: a primer for non-mathematicians, (Scribner, New York, 1981). Kranzler and J. Moursund, Statistics for the Terrified 2nd ed., (Prentice Hall, Upper Saddle River, 1999). F.K. Naylor and L.E. Enticknap, Statistics Simplified. An Introduction for Social Scientists and Others. (Harcourt Brace Jovanovich Group, Sydney, 1981). Motulsky, Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, (2nd ed.) (Oxford University Press, 2010). B. Orr, Fundamentals of Applied Statistics and Surveys, (Chapman and Hall, New York, 1995).