chelseaparlett

library(tidyverse)
library("viridis")
n <- 100
sd <- 10

cutoffz_r <- qnorm(0.975) * (sd/sqrt(n))
cutoffz_l <- -cutoffz_r

min_ES <- 0.28
min_raw <- min_ES*sd

chelseaparlett

# fake data
library(bayesAB)
library(MCMCpack)

plotInvGamma(2, 2.5) + geom_vline(xintercept = 1)

set.seed(8675309)
n <- 60
p <- 500

chelseaparlett

library(tidyverse)
library(rstan)
library(bayesplot)

#code
model_code <- "
data {
  int<lower = 2> K; // # of categories
  vector[K] priorprobs; //prior
  int<lower=0> n_total_1; //total in group 1

chelseaparlett

#---libs---------------------------------------------------
library(ltm)
library(jsonlite)
library(tidyverse)
library(patchwork)
library(stargazer)
library(rstan)
library(brms)
library(viridis)
library(plotly)

chelseaparlett

import time

def breath(prompt = "Hold------------"):
    print(prompt)
    time.sleep(1)
    for i in range(2,5):
        print(str(i))
        time.sleep(1)

breaths = 0

chelseaparlett

terms <- c("error", "random", "model",
           "mixed", "linear", "effects",
           "variance")
probs <- c(0.1,0.1, 0.55, 0.05, 0.05, 0.1, 0.05)

new_jargon <- sample(terms,
                     size = sample(c(2,3),1),
                     prob = probs) 
new_jargon <- paste(new_jargon, collapse = " ")

chelseaparlett

#libs--------------
library(grid)
library(tidyverse)
library(ggdark)
#funs--------------

irt <- function(a,b,c){
  theta <- seq(-10,10, length = 500)
  exponent <- exp(a*(theta-b))
  phat <- c + (1-c)*(exponent/(1 + exponent))

chelseaparlett

library(readr)
library(tidyverse)

# read in data
urlfile <- "https://raw.githubusercontent.com/Z-Unlocked/Unlocked_Challenge_1/main/temperature_change_data_11-29-2021.csv"

mydata <-read_csv(url(urlfile))

# filter
countries <- c("China", "Germany", "Japan", "United States of America")

chelseaparlett

library(tidyverse)
# create named list
l <- list(x = data.frame(a = rnorm(10), b = rnorm(10)),
                     y = data.frame(a = rnorm(10), b = rnorm(10)),
                                z = data.frame(a = rnorm(10), b = rnorm(10)))
          

for (i in names(l)){
  if (i %in% c("x", "y")){ # if the name of the list item is in a specified sublist
    l[[i]] <- l[[i]] %>% mutate(c = a + 1) # then do the mutate

chelseaparlett

from shiny import App, render, ui, reactive

from pathlib import Path

# Import modules for plot rendering
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd