From b4eaa1365c6708fe072548c307f98614ec11cf7a Mon Sep 17 00:00:00 2001 From: jacksonCL <43858469+jacksonCL@users.noreply.github.com> Date: Mon, 31 Jan 2022 08:50:55 -0700 Subject: [PATCH] Add Presentation and R Code --- .../Basic Stats with R.R | 115 ++++++++++++++++++ .../Basic Stats with R.pdf | Bin 0 -> 1021716 bytes 2 files changed, 115 insertions(+) create mode 100644 Lunchtime Basics-Basic Statistics using R/Basic Stats with R.R create mode 100644 Lunchtime Basics-Basic Statistics using R/Basic Stats with R.pdf diff --git a/Lunchtime Basics-Basic Statistics using R/Basic Stats with R.R b/Lunchtime Basics-Basic Statistics using R/Basic Stats with R.R new file mode 100644 index 0000000..1f7faf0 --- /dev/null +++ b/Lunchtime Basics-Basic Statistics using R/Basic Stats with R.R @@ -0,0 +1,115 @@ +###### CU Data Week ###### + +# Load Data +bweight <- read.csv("~/Downloads/bweight.csv") +birthwgt <- read.csv("~/Downloads/birthwgt.csv") +cars <- read.csv("~/Downloads/cars.csv") +class <- read.csv("~/Downloads/class.csv") + +########## Hypothesis 1 ######################################################## +# Birthweight and Smoking +################################################################################ + +# Summarize the data +library(tidyverse) + +# Difference in weights +bweight %>% group_by(MomSmoke) %>% summarise(Mean = mean(Weight), SD = sd(Weight)) +# 1 = Smoking; 0 = No Smoking + +# Other categories +library(table1) + +table1(~ MomWtGain + factor(MomEdLevel) + factor(Boy) | factor(MomSmoke), data = bweight) + + +########## Test 1: Relationship between Low birthweight and Maternal Smoking ### +table1(~ LowBirthWgt | Smoking, data = birthwgt) + +# We have some missing data, let's remove it +birthwgt <- birthwgt %>% filter(Smoking != "") + +table(birthwgt$LowBirthWgt, birthwgt$Smoking) + +# Chi-Square test +chisq.test(birthwgt$LowBirthWgt, birthwgt$Smoking, correct = F) +# We can say that low birth weigh and smoking are significantly associated + +############## Test 2: Relationship between birthweight and Maternal Smoking ### + +# How does the data look? +boxplot(bweight$Weight ~ bweight$MomSmoke) + +# Any missingness? +summary(bweight) # No! + +# What about the distribution? + +## qq plot +qqnorm(bweight %>% filter(MomSmoke == 1) %>% pull(Weight), pch = 1, frame = FALSE) +qqline(bweight %>% filter(MomSmoke == 1) %>% pull(Weight), col = "steelblue", lwd =1) + +qqnorm(bweight %>% filter(MomSmoke == 0) %>% pull(Weight), pch = 1, frame = FALSE) +qqline(bweight %>% filter(MomSmoke == 0) %>% pull(Weight), col = "steelblue", lwd =1) + +# Not happy about that QQ plot, let's go non-parametric + +wilcox.test(bweight$Weight ~ bweight$MomSmoke) +# Significant difference in birth weight + +# How is the t-test different? + +# We assume normality, we assume equal variance +var.test(bweight$Weight ~ bweight$MomSmoke) + +# By default, R will assume unequal variance +t.test(bweight$Weight ~ bweight$MomSmoke, var.equal = F) + + +########## Hypothesis 2 ######################################################## +# Cars and MPG +################################################################################ + +############## Test 1: Relationship between City MPG and Highway MPG ### + +hist(cars$MPG_Highway - cars$MPG_City) + +qqnorm(cars$MPG_Highway - cars$MPG_City, pch = 1, frame = FALSE) +qqline(cars$MPG_Highway - cars$MPG_City, col = "steelblue", lwd =1) + +wilcox.test(cars$MPG_Highway, cars$MPG_City, paired = T) + +# These are the same +t.test(cars$MPG_Highway, cars$MPG_City, paired = T) +t.test(cars$MPG_Highway - cars$MPG_City) +summary(lm(cars$MPG_Highway - cars$MPG_City ~ 1)) + + +########## Hypothesis 3 ######################################################## +# Weight and Height +################################################################################ + +############## Test 1: Relationship between weight and height ### + +# Look at the data +plot(class$Weight ~ class$Height) + +# normal? +hist(class$Weight) +hist(class$Height) + +# Fit a linear model +LM1 <- lm(class$Weight ~ class$Height) +summary(LM1) + +# Check our model +plot(LM1) +hist(LM1$residuals) + +# same results +cor.test(class$Weight, class$Height) + +# Not sure about the distribution? +cor.test(class$Weight, class$Height, method = "spearman") + + diff --git a/Lunchtime Basics-Basic Statistics using R/Basic Stats with R.pdf b/Lunchtime Basics-Basic Statistics using R/Basic Stats with R.pdf new file mode 100644 index 0000000000000000000000000000000000000000..c029bf1a921096edaf4646d6f28a1ccccc0eba97 GIT binary patch literal 1021716 zcmbq*cRbbY|9_67&OsdKSVbJ!o0L6{8D(Z>9?3{n_RcvOm6DV_Qz1J$`%p;=86oR5 ztWabVe(zKFeHWe2efR78Po2l{eqYz?dcO9!4yUe)nxLqV7&+(Tu`grO*$Ww+kDro@ zAw`g`XB^38Ws$;a=bSuk-GTp|tUYa2Y;9c6+9HKDZC&g=9gyPUVn}&;at}{;TWe=> zUy}0JRu_aKEd28(ZEV=ty|QB?@%(LUDaA+O`(BWojsm%dJf7S7IxHuamcXNgbZY%n zSh$`yop*2}%EN#bUlk8HHC8u@V62>r$d< zUGm_Aq$FL5^R?6gmlI2p^Km5uzU2L6T5t9(pLx9C63{RZygk3r9ra1!l7n~Gt10t< z3$dmx$B#I2wL 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