Course Outline
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segmentGetting Started (Don't Skip This Part)
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segmentStatistics and Data Science: A Modeling Approach
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segmentPART I: EXPLORING VARIATION
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segmentChapter 1 - Welcome to Statistics: A Modeling Approach
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segmentChapter 2 - Understanding Data
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segmentChapter 3 - Examining Distributions
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segmentChapter 4 - Explaining Variation
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segmentPART II: MODELING VARIATION
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segmentChapter 5 - A Simple Model
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segmentChapter 6 - Quantifying Error
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segmentChapter 7 - Adding an Explanatory Variable to the Model
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segmentChapter 8 - Digging Deeper into Group Models
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segmentChapter 9 - Models with a Quantitative Explanatory Variable
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segmentPART III: EVALUATING MODELS
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segmentChapter 10 - The Logic of Inference
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segmentChapter 11 - Model Comparison with F
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11.15 Chapter 11 Review Questions 2
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segmentChapter 12 - Parameter Estimation and Confidence Intervals
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segmentChapter 13 - What You Have Learned
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segmentFinishing Up (Don't Skip This Part!)
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segmentResources
list High School / Advanced Statistics and Data Science I (ABC)
Book
11.15 Chapter 11 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 hererequire(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)
# Boxplots 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_modelrequire(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)