PPT-Inference for Categorical Variables

Author : lois-ondreau | Published Date : 2018-03-18

22912 Single Proportion p Distribution Intervals and tests Difference in proportions p 1 p 2 One proportion or two Distribution Intervals and tests Section

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Inference for Categorical Variables: Transcript


22912 Single Proportion p Distribution Intervals and tests Difference in proportions p 1 p 2 One proportion or two Distribution Intervals and tests Section 61 62 63 67 68 69. 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. . Introduction; Displaying Distributions with Graphs. Statistics is... The science of data.. We begin our study of statistics by mastering the art of . examining data. Any set of data contains information about some group of individuals, organized by variables. . GCE Solutions. Derive Value From Excellence …. Issues with Common Outlier Detection Ideologies. Many are limited to numeric data only. Many are limited to Supervised data. What if you don’t have predictive data?. Thesis defense . 4/5/2012. Jaesik Choi. Thesis Committee: . Assoc. Prof. Eyal Amir (Chair, Director of research). Prof. Dan Roth. . Prof. Steven M. Lavalle. Prof. David Poole (University of British Columbia). Rodrigo de Salvo Braz. Ciaran O’Reilly. Artificial Intelligence Center - SRI International. Vibhav Gogate. University of Texas at Dallas. Rina Dechter. University of California, Irvine. IJCAI-16. , . Distinguish between:. - A statistic and a parameter. - A categorical and a quantitative variable. - A response and an explanatory . variable. Identify:. - When a categorical variable is ordinal. - When a quantitative variable is continuous. Section 1.1. Analyzing Categorical Data. The Practice of Statistics, 4. th. edition - For AP*. STARNES, YATES, MOORE. Chapter 1. Exploring Data. Introduction. :. . Data Analysis: Making Sense of Data. 1. Outline:. The contingency table. Independence and dependence. Hypothesis test for independence. The chi-square distribution. The “expected” table. The test statistic. Worked example. Categorical variables. 1. Outline:. The contingency table. Independence and dependence. Hypothesis test for independence. The chi-square distribution. The “expected” table. The test statistic. Worked example. Categorical variables. Professor Kari Lock Morgan. kari@stat.duke.edu. . Course Website:. http://stat.duke.edu/courses/Fall12/sta101.002/. Sakai:. https://sakai.duke.edu/portal/site/STAT101_Fall12. Course Website. Syllabus. Variables: The. Chi-Square . Test. Lecture PowerPoint Slides. Basic Practice of Statistics. 7. th. Edition. In Chapter 25, We . C. over …. Two-way tables. The problem of multiple comparisons. Expected counts in two-way tables. Find and interpret marginal and conditional distributions for 2 Categorical Variables. Determine if 2 Categorical Variables have a possible association. AP Statistics Objectives Ch3. frequency table. th. edition - For AP*. STARNES, YATES, MOORE. Chapter 1: Exploring Data. Introduction. Data Analysis: Making Sense of Data. Chapter 1. Exploring Data. Introduction. :. . Data Analysis: Making Sense of Data. 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...

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