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Introduction

In this report, we analyze the results of a survey conducted on employees within a company. The survey captures data related to employee satisfaction, work-life balance, and other important factors.

library(tidyverse) library(knitr) library(dplyr) survey <- read.csv(“survey.csv”)

knitr::opts_chunk$set(echo = TRUE)

knitr::opts_chunk$set(echo = TRUE)

Introduction

In this report, we analyze the results of a survey conducted on employees within a company. The survey captures data related to employee satisfaction, work-life balance, and other important factors.

Load Libraries and Data

{r setup_data, include=FALSE} library(tidyverse) library(knitr) library(dplyr) survey <- read.csv(“survey.csv”)

summary_stats <- survey %>% summarise( mean_satisfaction = mean(satisfaction, na.rm = TRUE), sd_satisfaction = sd(satisfaction, na.rm = TRUE) ) summary_stats

ggplot(survey, aes(x = satisfaction)) + geom_histogram(binwidth = 1, fill = “blue”, color = “black”) + labs(title = “Distribution of Employee Satisfaction”, x = “Satisfaction Score”, y = “Count”)

correlation <- cor(survey\(satisfaction, survey\)work_life_balance, use = “complete.obs”) correlation

satisfaction_by_dept <- survey %>% group_by(department) %>% summarise(mean_satisfaction = mean(satisfaction, na.rm = TRUE)) %>% arrange(desc(mean_satisfaction))

kable(satisfaction_by_dept)

By ensuring all chunks have unique names (like setup_data, task1_summary, etc.), this error should be resolved.