Publications by Ben Jaffe
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Use the purity-hydrocarbon data from Homework #2 and R to answer the following questions. The data are hosted on my github and the linke is provided on the WISE page. The purity of oxygen produced by a fractionation process is thought to be related to the percentage of hydrocarbons in the main condenser of the processing unity. Data for twenty s...
870 sym R (891 sym/14 pcs)
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Part One: Independent or Dependent Variables? 1. Use R to answer this set of questions. First, generate 1000 random numbers from the Uniform(0,1) distribution and call it X. Then generate another 1000 random numbers from the Uniform(0,1) distribution and call it Y. Let U = X - Y and V = X + Y. 1a. Are X and Y independent? Use a scatterplot and ...
5396 sym R (1902 sym/50 pcs) 15 img
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Problem 2: NFL Data Consider the first three variables, listed below, in the data concerning the performance of the 28 National Footbal Leagues in 1976. Y = games won (per 14-game season) x1 = rushing yards (per 14-game season) x2 = passing yards (per 14-game season) library(tidyverse) ## -- Attaching packages --------------------------------...
1600 sym R (34594 sym/55 pcs) 1 img
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Loading in the data. library(tidyverse) ## -- Attaching packages --------------------------------------- tidyverse 1.3.0 -- ## v ggplot2 3.3.3 v purrr 0.3.4 ## v tibble 3.0.6 v dplyr 1.0.3 ## v tidyr 1.1.2 v stringr 1.4.0 ## v readr 1.4.0 v forcats 0.5.1 ## -- Conflicts ------------------------------------------ tidyve...
1337 sym R (4873 sym/22 pcs)
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library(MASS) x <-c(22,52,60,42,47,65) y<-c(41, 49,69,55,60,62) Y Vector: Y <- matrix(c(41,49,69,55,60,62), nrow = 6, ncol = 1) Y ## [,1] ## [1,] 41 ## [2,] 49 ## [3,] 69 ## [4,] 55 ## [5,] 60 ## [6,] 62 Design Matrix X <- matrix(c(1,22,1,52,1,60,1,42,1,47, 1,65), nrow = 6, ncol = 2...
320 sym R (1407 sym/20 pcs) 1 img
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Problem 2: Summary Statistics Regression Puzzle A study uses a simple linear model to describe the relationship between the response variable Y and the explanatory variable x. Some key summary statistics. n <- 20 r<- (-0.85) sy<- 5 sx<- 6.78 y_bar <- 11.02 x_bar <- 9.28 a) Use the above statistics to report the least squares regression line...
885 sym R (353 sym/11 pcs)
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Data Description: Forbes’ Data on Boiling Points in the Alps For this part of the exam you will need to use the forbes dataset in the MASS package. A data frame with 17 observations on boiling point (bp) of water and barometric pressure (pres) in inches of mercury. According to chem.perdue.edu: - A liquid boils at a temperature at which its vap...
1925 sym R (1430 sym/16 pcs) 1 img
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fec<-read.csv("fec_independent_expenditures.csv", header = TRUE) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidyverse) ## -- Attaching packages...
992 sym R (3971 sym/26 pcs) 1 img
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Problem 2 Use the purity-hydrocarbon data from Homework #2 and R to answer the following questions. The data are hosted on my github and the link is provided on the WISE page. The purity of oxygen produced by a fractionation process is thought to be related to the percentage of hydrocarbons in the main condenser of the processing unity. Data fo...
4139 sym R (4928 sym/57 pcs) 1 img
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Milestone 3: Perform a Simple Linear Regression Using the same variables from Milestone 2. Continuing simple linear regression analysis: –Create an ANOVA table and produce the F-Statistic and discuss the R-Squared value. fec<-read.csv("fec_independent_expenditures.csv", header = TRUE) library(dplyr) ## ## Attaching package: 'dplyr' ## The...
1882 sym R (2252 sym/15 pcs) 4 img