Gaphs in Biostatistics

Anonymous
timer Asked: Feb 23rd, 2016

Question description

It is important to look at data in a graphical form. Patterns are the essence of data exploration, and the eye’s ability to discern forms and patterns makes visual display integral to the process. The visual display of quantitative information can help us see connections and relationships in the data, which are oftentimes difficult to detect in tables of numbers. We should look at data in a graphical form, and not rely solely on computational or statistical metrics.

In this discussion, we will explore graphs in linear regression. Our data are taken from an article by Frank Anscombe in a 1973 article in The American Statistician, which discusses scatterplots in relation to regression analyses.

First, download the dataset MHA610_Week 5_Discussion_Regression_Data.xls. This is a simple Excel workbook, with data on one sheet. There are eight columns of data, with headings X1, Y1, X2, Y2, X3, Y3, X4, Y4. Import the data into Statdisk using the MHA610_Week 5_Discussion_Regression_Data.CSV file, and perform the following analyses.

  • Calculate the regressions of Y1 on X1, Y2 on X2, Y3 on X3, and Y4 on X4, and compare the results (summary statistics). Explain what, if anything, you find unusual about these results.
  • Plot each set of data, along with the fitted regression line. Describe what the graphs tell you about the relationships between the X’s and the Y’s.
  • Explain what lessons you draw from this exercise.
Place the summary statistics and the plots in a separate Word document and attach that document to your initial post. Address the questions in the body of your initial discussion post.

mha610_week_5_discussion_regression_data.xls

Tutor Answer

(Top Tutor) Studypool Tutor
School: New York University
Studypool has helped 1,244,100 students
flag Report DMCA
Similar Questions
Hot Questions
Related Tags

Brown University





1271 Tutors

California Institute of Technology




2131 Tutors

Carnegie Mellon University




982 Tutors

Columbia University





1256 Tutors

Dartmouth University





2113 Tutors

Emory University





2279 Tutors

Harvard University





599 Tutors

Massachusetts Institute of Technology



2319 Tutors

New York University





1645 Tutors

Notre Dam University





1911 Tutors

Oklahoma University





2122 Tutors

Pennsylvania State University





932 Tutors

Princeton University





1211 Tutors

Stanford University





983 Tutors

University of California





1282 Tutors

Oxford University





123 Tutors

Yale University





2325 Tutors