Publications by StatsWithSarah
Week 5 - REAL
This week we learned about logistic regression, which can be used when predicting a variable with a binary response. Logistic regression equations are in the form of: log(p/(1-p)) = B0 + B1x1 + B2x2…. Below are a few practice problems that we did to understand the process. 5.3.1 Female Horseshoe Crab Weight Our logistic regression equation is:...
387 sym R (5296 sym/25 pcs)
Week 6
This week we learned more about logistic regression, which is used when you have a binomial response variable, like yes or no. Pretty much the same as last week, I’ll put in a few examples below that we did. Here is a problem we did for class on beer. beer <- read.csv("http://www.cknudson.com/data/MNbeer.csv") head(beer) ## Brewery ...
836 sym R (1686 sym/9 pcs)
Logistic Regression Quiz
A: Marijuana Model with All Predictors According to the summary Wald tests, Alcohol, Cigarettes, and Sex all appear to be significant at the 0.05 level. Alcohol appears to be the most significant variable. Race did not meet the 0.05 pvalue standard and appears to be the least influential variable. The coefficients for each variable will be in...
331 sym R (10943 sym/79 pcs)
PS02 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl); library(moments) set.seed(69) EXERCISE 01 Part (a) The mean is 5.2 v <- c(7,1,8,2,8) (v[1]+v[2]+v[3]+v[4]+v[5])/5 ## [1] 5.2 Part (b) The standard deviation is about 3...
1122 sym R (3805 sym/44 pcs) 2 img
PS01 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(69) EXERCISE 01 Part (a) library(readxl) MooseWolvesData <- read_excel("C:/Users/Sarah Chock/OneDrive - University of St. Thomas/Senior Year/STAT 360 Comp Stat ...
610 sym R (5285 sym/27 pcs)
PS14 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(37) EXERCISE 01 Part (a) We have 10 variance/covariance data points. 4*(4+1)/2 ## [1] 10 Part (b) We should fix the pathway from Healthcare Plan to Benefits to...
306 sym R (5086 sym/22 pcs) 2 img
PS13 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(37) EXERCISE 01 Part (a) mentalCov <- matrix(c(.165, .031, .055, .038, .031, .205, 0.089, 0.040, .055, 0.089, .165, .053, .038, 0.040, .053, .172), nrow = 4, nco...
291 sym R (3049 sym/18 pcs) 2 img
PS12 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(37) EXERCISE 01 Part (a) DCF <- matrix(c(1.00, -.72, -.09, -.38, -.72, 1.00, 0.23, 0.49, -.09, 0.23, 1.0, -.46, -.38, 0.49, -.46, 1.00), nrow = 4, ncol = 4) row...
296 sym R (4262 sym/23 pcs) 2 img
PS07 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(37) EXERCISE 01 Part (a) stonks <- matrix(c(0.00023, 0.00038, 0.00022, 0.00007, 0.00006, 0.00038, 0.00134, 0.00041, 0.00013, 0.00008, ...
430 sym R (4136 sym/32 pcs) 3 img
PS06 Solutions
STAT 360: Computational Statistics and Data Analysis Load R Libraries, Import and Attach Relevant Data, and Specify Seed library(rmarkdown); library(knitr); library(readxl) set.seed(37) EXERCISE 01 Part (a) poundToNewton <- function(pounds) { newt <- pounds*4.44822 return(newt) } Part (b) poundToNewton(70.59) ## [1] 313.9998 poundTo...
270 sym R (8407 sym/20 pcs) 1 img