Role of Statistics in Research - Report Example

Role of statistics in research Statistics plays a vital role in aiding researches through the collection and analysis of data and making inferences out of it. To be more specific, statistics is actually a branch of mathematics not just relating to theoretical concepts alone but, extensively used by researchers in numerous domains for organizing, analyzing, and summarizing the research data (Brown and Saunders 2007). Statistical methods and analysis are the strong tools used for communicating the findings of a research. Statistics supports the research hypotheses and enhances the credibility of the methodologies of research and the conclusions derived. Proper understanding of statistics is crucial for researchers and its consumers because, they can keep themselves aware by evaluating the credibility and practicality of the research and could make suitable decisions. In this report we would discuss about the role of statistics in research based on quantitative approaches and particularly its significance in the field of sports. For a research that is grounded on quantitative methodologies, statistics have a wide role to play in each and every stage of the research right from ground work preparation, collection of data, processing of the data, and deriving scientific conclusions. Quantitative methods deployed in researches rely on statistics which have a dominant role in expediting the accomplishment of the research objectives. Statistics have four major roles to play in a quantitative research. First, Statistics determines the sample research. Samples are the representatives of the entire research population and statistics provide the appropriate sampling techniques and formulas for obtaining the sample representatives of adequate size (Role of statistics 2011). Next, statistics helps in the development of the data retrieval tool. The reliability and validity of the research is dependent on the quality of the tools used for collecting the data. It is therefore essential to test the quality of the data collection tool. Statistical methods are the best means to verify the validity and reliability of the data collection tools. The next role of statistics in research is data presentation (Role of statistics 2011). Data collected from the previous process would be a raw data therefore it has to be converted into an understandable format in order to proceed with the research process. Descriptive statistics exclusively deals with quantitative data and provides methodologies for describing them (Heaton 2004). So, descriptive statistical methods aid in data processing and presentation. The final role of statistics is the analysis of data or otherwise testing of the hypotheses. Making an appropriate decision based on the conclusion derived is the ultimate goal of any research (Role of statistics 2011.). Statistics provides several calculation techniques and testing methods to validate the reliability and results of the research (Brown and Saunders 2007). Inferential statistics would be very much helpful for the researchers in this regard. The field of sports lends itself to statistical researches and analysis in huge number of ways. Performance of players are statistically analyzed for various purposes like probability of winning a match, how much goals or score a player may get in future tournaments, and so on. Say for example, the Society of American Baseball Research (SABR) focuses on statistically analyzed data popularly known as the ‘sabermetrics’ for recruiting the players (Luiselli and Reed 2011). Sabermetrics deals with the venture of maximizing the number of wins in matches through optimizing the financial resources by recruiting statistically significant players and not just the popular ones (Sports investing statistical). A players fielding, batting, and pitching statistics is calculated with the help of statistical formulas that would yield a percentage for each player which helps in evaluating the performance of a player (Statistics: growing point 2012). A player’s history of records regarding previous matches is collected and these collective and individual data are statistically analyzed to set a strategy level for each player. The impact of the player’s strategies and their combinations on the outcome of the match would be scrutinized to determine the probability of win in a match. Sabermetrics have set of formulas for calculating the performance metrics of the hitters, pitchers, and defenders (Lewis 2003). Few of those performance metrics are Runs Created (RC), On Base Percentage (OBP), Fielding Independent Pitching (FIP), Base Out Percentage (BOP), Total Average (TA), and many more (Statistics: growing point 2012). Baseball is not the only sport that relies on statistical researches. Statistical researches strongly influence many other sports like football, basketball, cricket, and others. The National Basketball Association (NBA) utilizes statistical analysis to evaluate, measure, and predict a player’s performance and percentage of wins though statistical methods like regression and correlation (Teramoto 2010). NBA makes use of both traditional performance evaluation factors like rebounds per game, field goal percentage and modern metrics like overall percentage and Four Factor (Teramoto, 2010). In general data taken for analysis in sports include the player’s physical qualities, player’s average percentage and economy that could contribute to the team’s win, and others. These data are collected for a reasonable period of time in the past. The collected data are exposed to statistical calculation methods like regression analysis, Monte Carlo simulation, and many more in order to calculate the ‘weight’ each player has on the optimal outcome of a match, what will be the projected score, will the team win or lose, and many more (Vose 2008). Statistical researches in the field of sports have become so much advanced. That is, in addition to predicting results of the matches through pre-assigned probabilities and combination of events, influence of the climatic conditions could also be included in the researches. Application of statistical research to sports is inevitable for the process of decision making. The significance of statistics could be better understood through high quality sports research. Statistical researches in sports aid in the rating and ranking of players and in setting the best strategy against an opponent team. The importance of statistic research in sports is emphasized by numerous scientific journals like the International Journal of Performance Analysis in Sport, the Journal of Sports Economics, and others (Statistics and sport 2004). Statistics have an evident role to play, not only in researches related to sports but also researches of almost any kind. Researchers incorporate statistics in their research methods which greatly aids them to formulate their hypotheses with the help of empirical evidences. Statistics is an invaluable tool for researchers because it helps them to condense a large quantity of data into meaningful information. References Brown, RB and Saunders, M., 2007. Dealing with Statistics: What You Need To Know: What you need to know. McGraw-Hill Education (UK). Heaton, J., 2004. Reworking Qualitative Data. SAGE. Lewis, M., 2003. Moneyball: The Art of Winning an Unfair Game. W. W. Norton. Luiselli, JK and Reed, DD., 2011. Behavioral Sport Psychology: Evidence-Based Approaches to Performance Enhancement. Springer Science & Business Media. Role of statistics in quantitative research., n. d. Available from: http://management- statistics.blogspot.in/2011/02/role-of-statistics-in-quantitative.html(accessed on 11 May 2015) Sports Investing Statistical Significance., n. d. Available from: https://www.sportsinsights.com/sports-investing-statistical-significance/(accessed on 11 May 2015) Statistics and sport :Moneyballs., 2004. Available from: http://www.economist.com/node/2494781(accessed on 11 May 2015) Statistics: growing point of reference in sports., 2012. Available from: http://tisconsulting.org/news/statistics-growing-point-of-reference-in- sports/(accessed on 11 May 2015) Teramoto, M., 2010. Application of statistics in sports: Predicting how teams win in NBA. Available from: http://www.wskw.org/node/28(accessed on 11 May 2015) Vose, D., 2008. Risk Analysis: A Quantitative Guide. 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