Practical guides : Statistics for Biologists.
Determinación del tamaño muestral. Todo estudio epidemiológico lleva implícito en la fase de diseño la determinación del tamaño muestral necesario para la ejecución del mismo (1-4). El no realizar dicho proceso, puede llevarnos a dos situaciones diferentes: primera que realicemos el estudio sin el número adecuado de pacientes, con lo cual no podremos ser precisos al estimar los parámetros y además no encontraremos diferencias significativas cuando en la realidad sí existen. La segunda situación es que podríamos estudiar un número innecesario de pacientes, lo cual lleva implícito no solo la pérdida de tiempo e incremento de recursos innecesarios sino que además la calidad del estudio, dado dicho incremento, puede verse afectada en sentido negativo. Para determinar el tamaño muestral de un estudio, debemos considerar diferentes situaciones (5-7): A. Estudios para determinar parámetros. Es decir pretendemos hacer inferencias a valores poblacionales (proporciones, medias) a partir de una muestra (Tabla 1).
Interactive Statistical Calculation Pages. Curso SPSS. Odds ratio calculator. QuickCalcs. MIDAS - Sensitivity and Specificity Calculator. ROC. OpenEpi--Epidemiologic Calculators. R Tutorials--Logistic Regression. Preliminaries Model Formulae You will need to know a bit about Model Formulae to understand this tutorial. Odds, Odds Ratios, and Logit When you go to the track, how do you know which horse to bet on? You look at the odds. In the program, you may see the odds for your horse, Sea Brisket, are 8 to 1, which are the odds AGAINST winning.
P(one outcome) p(success) p odds = -------------------- = ----------- = ---, where q = 1 - p p(the other outcome) p(failure) q So for Sea Brisket, odds(winning) = (1/9)/(8/9) = 1/8. The natural log of odds is called the logit, or logit transformation, of p: logit(p) = loge(p/q). If odds(success) = 1, then logit(p) = 0. Logistic regression is a method for fitting a regression curve, y = f(x), when y consists of proportions or probabilities, or binary coded (0,1--failure,success) data. Y = [exp(b0 + b1x)] / [1 + exp(b0 + b1x)] Logistic regression fits b0 and b1, the regression coefficients (which were 0 and 1, respectively, for the graph above). I'm impressed! How To Determine Sample Size, Determining Sample Size. In order to prove that a process has been improved, you must measure the process capability before and after improvements are implemented. This allows you to quantify the process improvement (e.g., defect reduction or productivity increase) and translate the effects into an estimated financial result – something business leaders can understand and appreciate.
If data is not readily available for the process, how many members of the population should be selected to ensure that the population is properly represented? If data has been collected, how do you determine if you have enough data? Determining sample size is a very important issue because samples that are too large may waste time, resources and money, while samples that are too small may lead to inaccurate results. When sample data is collected and the sample mean is calculated, that sample mean is typically different from the population mean . Is the maximum difference between the observed sample mean where: is the sample size. . . Effect Size Calculators | University of Colorado Colorado Springs. RStats Resources - RStats Institute. Statistics Tutoring Undergraduate students who need assistance with statistics homework can receive one-on-one tutoring through Missouri State University's Bear CLAW (Center for Learning and Writing).
Click here to access Bear CLAW Statistics Tutoring. Instructional Videos Tables and Calculators Click here to access: Normal Distribution TableT Distribution TableCritical Pearson's r ValuesF Distribution TableChi Square Distribution Table and CalculatorCohen's D Effect Size Calculator Notes from Previous RStats Workshops Information About RStats. Interactive Statistical Calculation Pages. StatCrunch - Data analysis on the Web. SISA allows you to do statistical analysis directly on the Internet. Bioestadistico.com. VassarStats: Statistical Computation Web Site. T-Tests. StatThink - Statistical Thinking Diagrams and Models.
From: Pfannkuch, M., Regan, M., Wild, C. and Horton, N.J. (2010) Telling Data Stories: Essential Dialogues for Comparative Reasoning.Journal of Statistics Education, 18(1). Looking at data Download as a png or an eps From: Forster, M. and Wild, C. Writing about findings: Integrating teaching and assessment. In, Assessment Methods in Statistical Education, P. Bidgood, N. Data analysis cycle Download as a png or an eps From: : Wild, C.J. and Pfannkuch, M. (1999) "Statistical thinking in empirical enquiry" (with discussion). Learning via statistics Download as a png or an eps Investigative Cycle (Statistical investigation cycle/PPDAC cycle) Download as a png or an eps Types of Thinking Download as a png or an eps Interrogative Cycle Download as a png or an eps Dispositions Download as a png or an eps From Inkling to Plan Download as a png or an eps Shuttling between the spheres Download as a png or an eps Using any technique Download as a png or an eps Distillation and Encapsulation Making Connections.