Course Outline

list High School / Statistics and Data Science II (XCD)

Book
  • High School / Advanced Statistics and Data Science I (ABC)
  • High School / Statistics and Data Science I (AB)
  • High School / Statistics and Data Science II (XCD)
  • High School / Algebra + Data Science (G)
  • College / Introductory Statistics with R (ABC)
  • College / Advanced Statistics with R (ABCD)
  • College / Accelerated Statistics with R (XCD)
  • CKHub: Jupyter made easy

5.15 Chapter 5 Review Questions 2

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require(coursekata) link <- "https://docs.google.com/spreadsheets/d/e/2PACX-1vSZozH-r8y8XkIQ71eLTKL94R8Unkw41KqCJFmbvRlU-jcphybc4X_WVNZTvAH1_-4l4tx7wWSIH0Rk/pub?output=csv" san_andreas <- read.csv(link, header=TRUE) san_andreas$experience <- as.factor(san_andreas$experience) san_andreas$will_occur <- as.factor(san_andreas$will_occur) san_andreas$worry_general <- recode(san_andreas$worry_general, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$worry_bigone <- recode(san_andreas$worry_bigone, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$experience <- factor(san_andreas$experience, levels = c("No", "Yes, one or more minor ones", "Yes, one or more major ones")) san_andreas <- na.omit(san_andreas) # run your code here
require(coursekata) link <- "https://docs.google.com/spreadsheets/d/e/2PACX-1vSZozH-r8y8XkIQ71eLTKL94R8Unkw41KqCJFmbvRlU-jcphybc4X_WVNZTvAH1_-4l4tx7wWSIH0Rk/pub?output=csv" san_andreas <- read.csv(link, header=TRUE) san_andreas$experience <- as.factor(san_andreas$experience) san_andreas$will_occur <- as.factor(san_andreas$will_occur) san_andreas$worry_general <- recode(san_andreas$worry_general, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$worry_bigone <- recode(san_andreas$worry_bigone, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$experience <- factor(san_andreas$experience, levels = c("No", "Yes, one or more minor ones", "Yes, one or more major ones")) san_andreas <- na.omit(san_andreas) # Box Plots and Histograms gf_boxplot(worry_bigone ~ experience, data = san_andreas) gf_histogram(~worry_bigone, data = san_andreas, bins = 5) %>% gf_facet_grid(experience~.) # Write some code to fit and save exp_model
require(coursekata) link <- "https://docs.google.com/spreadsheets/d/e/2PACX-1vSZozH-r8y8XkIQ71eLTKL94R8Unkw41KqCJFmbvRlU-jcphybc4X_WVNZTvAH1_-4l4tx7wWSIH0Rk/pub?output=csv" san_andreas <- read.csv(link, header=TRUE) san_andreas$experience <- as.factor(san_andreas$experience) san_andreas$will_occur <- as.factor(san_andreas$will_occur) san_andreas$worry_general <- recode(san_andreas$worry_general, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$worry_bigone <- recode(san_andreas$worry_bigone, "Not at all worried" = 1, "Not so worried" = 2, "Somewhat worried" = 3, "Very worried" = 4, "Extremely worried"= 5) san_andreas$experience <- factor(san_andreas$experience, levels = c("No", "Yes, one or more minor ones", "Yes, one or more major ones")) san_andreas <- na.omit(san_andreas) exp_model <- lm(worry_bigone ~ experience, data = san_andreas) # Run this code pairwise(exp_model)

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