Interpret the pearson correlation coefficient

Info icon This preview shows pages 20–23. Sign up to view the full content.

View Full Document Right Arrow Icon
± Interpret the Pearson Correlation Coefficient describing the strength and direction of the linear relationship between variables. ± Compute linear regression models and interpret them. ± Interpret correlation tables. Contextual Learning Objectives Using the content, students will be able to do the following: ± Create models for the relationship between the insurance claim amount for a household based on its distance from the ocean and the category of storm that hits. ± Analyze correlation tables to determine key variables related to the magnitude of insurance claims (square footage, material home is made of, elevation, etc.). ± Analyze recent trends in tropical storms and hurricanes in the U.S. Common Core State Standards for Mathematics Interpreting Categorical and Quantitative Data (S-ID) ± Summarize, represent and interpret data on two categorical and quantitative variables. ± Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. 6. Fit a function to the data; use functions fitted to data to solve problems in the context of data. Use given functions or choose by the context. Emphasize linear, quadratic and exponential models. a. Informally assess the fit of a function by plotting and analyzing residuals. b. Fit a linear function for a scatterplot that suggests a linear association.
Image of page 20

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Page 21 MODULE 4 ± Interpret linear models 7. Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. 8. Compute (using technology) and interpret the correlation coefficient of linear fit. 9. Distinguish between correlation and causation. Materials Needed Much of the work in this module can be accomplished through the student handouts. Presentation format can vary. The lesson can be teacher directed or students can work in small groups. Although not required, students may wish to use the statistical capabilities of graphing calculator technology (TI-83/84). Students can also use statistical functions in spreadsheet programs such as Microsoft Excel. Guidelines and general instructions for using these tools are provided in the student modules in the Technology Connections section. Timing This module is designed to take 1–3 class periods depending on the depth desired. Definitions ± Scatterplot —the most common graph for looking at the relationship between two quantitative variables ± Response variable —the y-axis on a scatterplot ± Explanatory variable —the x-axis on a scatterplot ± Correlation coefficient —a measure of the strength and direction of the linear relationship between two quantitative variables ± Linear regression —a predictive model that creates a line of best fit for a set of data points ± Correlation table —a table showing the correlations between every pair of variables in a collection of variables
Image of page 21
Page 22 MODULE 4 Discussion Question Plot each of these points [as found in the student guide] on this graph: (p. 27) 1 x x x 2 x x x 3 x x x 4 x x x 5 x x x 6 x x x 7 x x x
Image of page 22

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 23
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern