PPT-HOW-113 Exploring Sampling Distributions with SAS Studio: An Activity for Statistics Educators

Jonathan W Duggins James Blum NC State University UNC Wilmington Agenda Introduction SAS Studio Basics Tasks Snippets Editing Code Summary Introduction Motivation Guidelines for Assessment and Instruction in Statistics Education GAISE. Data Collection & Sampling Techniques . Objectives. Identify the five basic sample techniques . Data Collection. In research, statisticians use data in many different ways. . Data can be used to describe situations. . Understanding the meaning of the terminology we use.. Quick calculations that indicate understanding of the basis of methods.. Many of the possible questions are already sprinkled in the lecture slides.. R. andom . T. rees . (RRTs). for Efficient Motion Planning. RSS Lecture . 10. Mon. day. , . 10 . March . 2014. Prof. Seth Teller. (Thanks to . Sertac. . Karaman. for animations). Recap of Previous Lectures:. 1. SAMPLING DISTRIBUTIONS —. SAMPLING DISTRIBUTIONS. Population and samples, parameters and statistics. A . POPULATION. is the set of . all possible subjects . of a given . experiment. or . study. Highlights:. The law of large numbers. The central limit theorem. Sampling distributions. Formalizing the central limit theorem. Calculating probabilities associated with sample means. Two important results in inferential statistics. Parameter & Statistic. Parameter. Summary measure about population. Sample Statistic. Summary measure about sample. P. . in. . P. opulation. . &. . P. arameter. S. . in. . S. ample. . and Estimators. EXAMPLE . Because of rude sales personnel, a poor business plan, ineffective advertising, and a poor name, Polly Esther’s Fashions was in business only three days. On the first day 1 dress was sold, 2 were sold on the second day, and only 5 were sold on the third day. Because 1, 2, and 5 are the entire population, the mean is . Lecture Presentation Slides. Macmillan Learning ©. 2017. Chapter 5. Sampling . Distributions. 5.1 Toward Statistical Inference. 5.2 The Sampling Distribution of a Sample Mean. 5.3 Sampling Distributions for Counts and . 7. Introduction. In . a typical statistical inference problem, you want to discover one or more characteristics of a given population. .. However, it is generally difficult or even impossible to contact each member of the population.. William P. Wattles, Ph.D.. I got the job!!! I am the new Human Resource Recruitment Specialist for . …I . would be involved in all branches. BEST PART... most of my job has to do with job analysis and performance, retention and turnover trends! (ALL STATISTICS and Behavior analysis) I will always apply what I learned at Francis Marion . Objectives. In this chapter, you learn:. The concept of the sampling distribution. To compute probabilities related to the sample mean and the sample proportion. The importance of the Central Limit Theorem. Lecture PowerPoint Slides. Basic Practice of Statistics. 7. th. Edition. In chapter 15, we cover …. Parameters and statistics. Statistical estimation and the Law of Large Numbers. Sampling distributions. AP Statistics Chapter 1 - Review 2013 Mrs. White AP ExamTopic Outline Topic Exam Percentage Exploring Data 20%-30% Sampling & Experimentation 10%-15% Anticipating Patterns 20%-30% Statistical Inference s. for . Activity Recognition . in Body Sensor Networks. Xin. Qi. , Matthew . Keally. , Gang Zhou, . Yantao. Li, Zhen . Ren. College of William and Mary. 1. http://www.cs.wm.edu/~xqi. RTAS 2013. Background - Activity Recognition.