http://www.merlot.org:80/merlot/ A search of MERLOT materials Copyright 1997-2013 MERLOT. All rights reserved. Sat, 18 May 2013 16:40:06 PDT Sat, 18 May 2013 16:40:06 PDT http://www.merlot.org:80/merlot/images/merlot.gif http://www.merlot.org:80/merlot/ 44 34 http://www.merlot.org/merlot/viewMaterial.htm?id=84322 An interactive multimedia tutorial for healthcare professionals wishing to refresh math skills and learn how to calculate medication dosages and intravenous (IV) rates. The tutorial has three modules. Each module has includes a quiz. The first module covers information about fractions, decimals, ratios, proportions, and percentage. The second module covers information about conversions, medication administration, and dosage calculation. The third module covers information about intraveneous infusions including tubing calculation and intraveneous flow rates. Key words: Medication calculation; Intravenous flow rate calculation; Mathematics principles http://www.merlot.org/merlot/viewMaterial.htm?id=327642 Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations. Learning Objectives The goal of this course is to equip biostatistics and quantitative scientists with core applied statistical concepts and methods:1) The course will refresh the mathematical, computational, statistical and probability background that students will need to take the course.2) The course will introduce students to the display and communication of statistical data. This will include graphical and exploratory data analysis using tools like scatterplots, boxplots and the display of multivariate data. In this objective, students will be required to write extensively.3) Students will learn the distinctions between the fundamental paradigms underlying statistical methodology.4) Students will learn the basics of maximum likelihood.5) Students will learn the basics of frequentist methods: hypothesis testing, confidence intervals.6) Students will learn basic Bayesian techniques, interpretation and prior specification.7) Students will learn the creation and interpretation of P values.8) Students will learn estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates.9) Students will learn estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences.10) Students will learn the basic concepts of ANOVA. http://www.merlot.org/merlot/viewMaterial.htm?id=730142 This is a free course offered as part of the Saylor Foundation's Professional Development program. 'This program is designed especially for adult learners who are ready to learn and apply skills demanded by today’s employers. Whether you are new to the employment world or wish to develop and improve your workplace skills, you will be able to select short-term courses targeted to your success.''Though accounting may seem like a dense and complex subject, this course is designed to present the accounting cycle in an accessible and logical manner. This course will provide you with a solid understanding of basic accounting principles and will introduce you to financial statement analysis. Please note that this course is the first of two courses on the principles of accounting and that each of these two courses is divided into 10 units. Each unit should take approximately three hours to complete and should be completed sequentially for the most logical progression of information. As you work through these units, you will encounter a range of examples and problem sets geared towards providing you with practical applications of the lessons you learn. By the end of this course, you will able to create accurate and appropriate financial statements to convey a company’s financial health.This course begins with an introduction to financial accounting and the various ways in which financial statements allow companies to make intelligent economic decisions. All companies, large and small, prepare financial statements in accordance with specific accounting rules that investors use to determine which stocks are attractive to buy. Accounting principles and financial statements are equally important for companies that do not have public stock available for investors to buy. You will learn all about these statements, the accounting rules that govern them, and the governing bodies that are responsible for accounting oversight.Later in the course, you will be immersed in the details of accounts receivables, inventory, and liabilities. Understanding the link among these components is vital to drawing accurate conclusions about financial statements and making reliable recommendations for improving profitability.This course concludes with two units focused on the analyses of financial statements, which will also introduce several mathematical ratios. The accurate use of these ratios is vital to drawing intelligent conclusions about a company’s operation practices and profitability. Even billionaire stock investor Warren Buffet uses financial-statement analysis to determine his next $100 million stock purchase.The goal of this course is to provide you with a solid foundation of accounting principles so that you can apply this knowledge to real-world accounting examples and be able to comfortably decipher a company’s financial statements and viability.' http://www.merlot.org/merlot/viewMaterial.htm?id=327650 Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations. Learning Objectives The goal of this course is to equip biostatistics and quantitative scientists with core applied statistical concepts and methods:1) The course will refresh the mathematical, computational, statistical and probability background that students will need to take the course.2) The course will introduce students to the display and communication of statistical data. This will include graphical and exploratory data analysis using tools like scatterplots, boxplots and the display of multivariate data. In this objective, students will be required to write extensively.3) Students will learn the distinctions between the fundamental paradigms underlying statistical methodology.4) Students will learn the basics of maximum likelihood.5) Students will learn the basics of frequentist methods: hypothesis testing, confidence intervals.6) Students will learn basic Bayesian techniques, interpretation and prior specification.7) Students will learn the creation and interpretation of P values.8) Students will learn estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates.9) Students will learn estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences.10) Students will learn the basic concepts of ANOVA.