PPT-Sample Size for Categorical Data

Binary Ordinal and Contingency Table Data Ronan Fitzpatrick Lead Statistician nQuery Webinar Host Agenda Categorical Data Overview Binary Data Methods amp Sample Size Ordinal Data Methods amp Sample Size. ca Abstract Categorical datafrequency data and discrete dataare most of ten presented in tables and analyses using loglinear models and logistic regression are most often presented in terms of parame ter estimates Over the past decade I and others ha Some vocab . Statistics. . is . the. art of solving problems and answering questions by collecting and analysing data.. Data . are the facts or information we collect and analyze. (plural). (. note datum is the singular term). –. some random observations. PSI, 2. nd. November 2016. Simon Day. s. imon.day@CTCT-Ltd.co.uk. The plan. …. I was an author on one of the very early papers on sample size re-estimation (Birkett and Day, . Categorical data. Some variables are inherently categorical, for example:. Sex. Race. Occupation. Other categorical variables are created by grouping values of a quantitative variable into classes. . An attribute is a property or. characteristic of an object. Examples: eye color of a. person, temperature, etc.. An Attribute is also known as variable,. field, characteristic, or feature. A collection of attributes describe an object. A random sample of 32 individuals from the 2000 US Census is shown to the left.. 1.) How old is the youngest person in the sample? The oldest?. 2.) About what percent of the sample is 65 or older?. 3.) about what percent of the population is younger than 65? Justify your answer. . . Jenny C. Aker. Tufts University. What affects the sample size?. Effect Size. Variance. Sample. Size. Significance. Level. Power. Proportion in. Treatment. Variance in outcome Y. 2/29/12. Single Proportion, . p. . Distribution. Intervals and tests. Difference in proportions, . p. 1. – p. 2. . One proportion or two?. Distribution. Intervals and tests. Section 6.1, 6.2, 6.3, 6.7, 6.8, 6.9. Introduction. Data Analysis: Making Sense of Data. After this section, you should be able to…. DEFINE “Individuals” and “Variables”. DISTINGUISH between “Categorical” and “Quantitative” variables. Statistical Questions. Statistical Questions. : ones that can be answered by collecting and analyzing . data. (pieces of information, can be numerical or categorical). Ex’s:. (a) What is the height of each . Sampling error is acknowledgedClaims/Inferences indicate that a sample may or may not be representative of the larger population Interpretations include the difference between two groups with differe What is STATISTICS?. Statistics . fulfill one . of the basic human . needs.. A. . process . to: . Manage. . -. . to clean and format the data in order to get a valid data which is feasible to be analyzed. Collecting Data in a Study. sample survey: . sample people from a population and interview them.. example. : General Social Survey . . experiment: . compare responses of subjects under different conditions, with subjects assigned to the conditions.. 1. STAT 101Exploratory Data Analysis I1/25/12 One Categorical Variable Two Categorical Variables One Quantitative Variable – CenterSection 2.1, 2.2Professor Kari Lock MorganDuke University2. AnnouncementsTextbooks are here!My office hours: (Old...