Publications by BayesianN
An almost ready public health thesis
Introduction Neonatals death refers to the death of newborns before they turn 28 days old (Usman et al.,2019), and can be categorized as early or late depending on whether the death occurred before or after the seventh day of life. The period after birth is widely regarded as the most vulnerable and high-risk time for newborns. This is due to t...
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definitely a public health work in progress of my thesis
Introduction Neonatals death refers to the death of newborns before they turn 28 days old (Usman et al.,2019), and can be categorized as early or late depending on whether the death occurred before or after the seventh day of life. The period after birth is widely regarded as the most vulnerable and high-risk time for newborns. This is due to t...
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Thesis work in Progress
Introduction Neonatals death refers to the death of newborns before they turn 28 days old (Usman et al.,2019), and can be categorized as early or late depending on whether the death occurred before or after the seventh day of life. The period after birth is widely regarded as the most vulnerable and high-risk time for newborns. This is due to t...
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this work in progress of my thesis
Introduction Neonatals death refers to the death of newborns before they turn 28 days old (Usman et al.,2019), and can be categorized as early or late depending on whether the death occurred before or after the seventh day of life. The period after birth is widely regarded as the most vulnerable and high-risk time for newborns. This is due to t...
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summary of my thesis
1 Introduction Neonatals death refers to the death of newborns before they turn 28 days old (Usman et al.,2019), and can be categorized as early or late depending on whether the death occurred before or after the seventh day of life. The period after birth is widely regarded as the most vulnerable and high-risk time for newborns. This is due to...
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direct comparison of R and SQL
Loading data The Notebook is divided into tabbed sections as seen below. loading data in R sales<-tribble(~ year , ~country , ~product , ~profit ,~Own ,~Time, 2000 , "Finland", "Computer" , 1500 ,"Y" ,"D", 2000 , "Finland" ,"Phone" , 100 ,"Y" ,"D", 2001 , "Finland" ,"Phone" ...
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fun to read but still under construction-Modeling
Introduction The Notebook is divided into tabbed sections as seen below. Purpose our business problem is: We have stagnant profit because the number of sales is constant There are a lot of customer leads but we can’t reach all of them We need to know which customer leads that should be prioritized We need lead scoring so that we can be effic...
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important functions for string manipulation
introduction most data cleaning processes involve working with structured and unstructured character/string datatypes . the ability to manipulate string data can be a super power Load in the necessary packages library(tidyverse) library(odbc) library(DBI) library(RSQLite) create a fake dataset in R using tribble() original_table<-tribble(~co...
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Answering complex business questions using SQL
tools evolve CREATE TABLE sales ( "customer_id" VARCHAR(1), "order_date" DATE, "product_id" INTEGER ); INSERT INTO sales ("customer_id", "order_date", "product_id") VALUES ('A', '2021-01-01', '1'), ('A', '2021-01-01', '2'), ('A', '2021-01-07', '2'), ('A', '2021-01-10', '3'), ('A', '2021-01-11', '3'), ('A', '2021-0...
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job retention analysis
Library Setup library(tidyverse) library(knitr) library(gtsummary) library(ggpubr) library(RColorBrewer) library(lemon) library(paletteer) library(survival) library(survminer) library(cowplot) library(rms) library(car) library(patchwork) options("encoding" = "UTF-8") knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE...
17947 sym Python (22615 sym/32 pcs) 12 img 1 tbl