The Calculus I course was developed through the Ohio Department of Higher …

The Calculus I course was developed through the Ohio Department of Higher Education OER Innovation Grant. This work was completed and the course was posted in February 2019. The course is part of the Ohio Transfer Module and is also named TMM005. For more information about credit transfer between Ohio colleges and universities, please visit: transfercredit.ohio.gov.Team LeadJim Fowler Ohio State UniversityRita Ralph Columbus State Community CollegeContent ContributorsNela Lakos Ohio State UniversityBart Snapp Ohio State UniversityJames Talamo Ohio State UniversityXiang Yan Edison State Community CollegeLibrarianDaniel Dotson Ohio State University Review TeamThomas Needham Ohio State UniversityCarl Stitz Lakeland Community CollegeSara Rollo North Central State College

After completing this section, students should be able to do the following.Use …

After completing this section, students should be able to do the following.Use limits to find the slope of the tangent line at a point.Understand the definition of the derivative at a point.Compute the derivative of a function at a point.Estimate the slope of the tangent line graphically.Write the equation of the tangent line to a graph of a function at a given point.Recognize and distinguish between secant and tangent lines.Recognize the the tangent line as a local approximation for a differentiable function near a point.

By the end of this section, you will be able to: Interpret …

By the end of this section, you will be able to:

Interpret production possibilities frontier graphs Contrast a budget constraint and a production possibilities frontier Explain the relationship between a production possibilities frontier and the law of diminishing returns Contrast productive efficiency and allocative efficiency Define comparative advantage

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

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

No restrictions on your remixing, redistributing, or making derivative works. Give credit to the author, as required.

Your remixing, redistributing, or making derivatives works comes with some restrictions, including how it is shared.

Your redistributing comes with some restrictions. Do not remix or make derivative works.

Most restrictive license type. Prohibits most uses, sharing, and any changes.

Copyrighted materials, available under Fair Use and the TEACH Act for US-based educators, or other custom arrangements. Go to the resource provider to see their individual restrictions.