A series of lectures delivered by Peter Millican to first-year philosophy students …
A series of lectures delivered by Peter Millican to first-year philosophy students at the University of Oxford. The lectures comprise of the 8-week General Philosophy course, delivered to first year undergraduates. These lectures aim to provide a thorough introduction to many philosophical topics and to get students and others interested in thinking about key areas of philosophy. Taking a chronological view of the history of philosophy, each lecture is split into 3 or 4 sections which outline a particular philosophical problem and how different philosophers have attempted to resolve the issue. Individuals interested in the 'big' questions about life such as how we perceive the world, who we are in the world and whether we are free to act will find this series informative, comprehensive and accessible.
Introductory statistics course developed through the Ohio Department of Higher Education OER …
Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.Team LeadKameswarrao Casukhela Ohio State University – LimaContent ContributorsEmily Dennett Central Ohio Technical CollegeSara Rollo North Central State CollegeNicholas Shay Central Ohio Technical CollegeChan Siriphokha Clark State Community CollegeLibrarianJoy Gao Ohio Wesleyan UniversityReview TeamAlice Taylor University of Rio GrandeJim Cottrill Ohio Dominican University
Sometimes it is difficult to measure or find information on a variable …
Sometimes it is difficult to measure or find information on a variable of interest. The problem then is to use information from easily measurable variables to find the needed information. Naturally, the variables to use must be related to the variable of interest. In this module we will study about relationships between two quantitative variables. We will explore some standard mathematical (linear, quadratic, cubic, etc.) forms of relationships.Learning Objectives:Identify response and explanatory variablesGiven bivariate data make a scatterplot of data and predict the pattern and strength of the relationship between the variablesLinear relationshipDefine correlation, study its properties and use themFind correlation for a bivariate data and interpret the resultsInterpret the square of the correlationTest for the significance of correlation – set up hypothesis and interpret the p-value of the testLinear relationship – Estimate the linear relationship between the two variables.Interpret slope and intercept.Interpret the square of the correlationStudy residuals and residual plots,Distinguish between the terms correlation and causationTest for the significance of the slope coefficient – set up hypothesis and interpret the p-value of the test.Study quadratic and other non-linear models.Textbook Material - Chapter 12 – Correlation and Regression – Pages 673 - 699
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