Midterm Take Home Test Dr DH Jones 2020-10-12 Instructions Individual work This is an unproctored examination in the form of a real data analysis project.It is expected that all your work is only your work: you may not consult for any reason with other student, staff, faculty, or live internet entities.You may use lecture notes, books, or internet libraries.You will be required to download and electronically sign the honor certificate, and then upload it to Canvas.Your exam will not be graded until you have met the honor certificate requirement. Uploading your work There will be eight(8) canvas assignment slots: one for the honor certificate, and seven for the test questions.Therefore, in effect, you must prepare seven source files for each question with each file containing the code to load and rename the data.You will upload your answers to each question individually to Canvas.Your files must be in HTML format as generated from RStudio.Please do not email your answers to the professor. R Code Show all your R code for each question that calls for coding.If the coding is missing, you will not receive credit for that portion of the test. Data The dataset for analysis is GaltonFamilies in the HistData package using a statistical linear model.In the 1880âs, Francis Galton, inventor of the concept of correlation, assembled the dataset as part of his ground-breaking research and applications of regression analysis. R code for loading and renaming the data For each question, use the following R code to obtain and rename the data. # install.packages(“HistData”, repos = “http://cran.us.r-project.org”, dependencies=TRUE) # After the first compile, you may comment out this line. library(“HistData”) data(GaltonFamilies) Galton2
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