Introduction to Psychological Research Methods.Rmd

---
title: 'PSY173: Introduction to Psychological Research Methods'
date: "2/19/2023"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


# Data Import

```{r, message=FALSE, warning=FALSE}
library(readr)
data <- read_csv("C:/Users/Admins/Desktop/R/data/my_data.csv")
```


# Normality testing

```{r}
# Conduct normality testing using the Shapiro-Wilk test
shapiro.test(data$Participants)
shapiro.test(data$Group)
shapiro.test(data$`Dependent variable`)
shapiro.test(data$`Range of group-low`)
shapiro.test(data$`Range of group-high`)
```
# Describe statistics

```{r}
# Present descriptive statistics
library(psych)
describe(data)
```

#inferntial statistics

```{r}
summary(data)
```


```{r}
# Create a scatter plot with all columns and add a legend
par(mfrow = c(1, 1))
plot(data$Participants, col = "lightblue", pch=16, main = "Scatter Plot of individual observations", xlab = "Participants", ylab="Value")
points(data$Group, col = "pink", pch=16)
points(data$`Dependent variable`, col = "lightgreen", pch=16)
points(data$`Range of group-low`, col = "lightyellow", pch=16)
points(data$`Range of group-high`, col = "lavender", pch=16)
legend("topright", c("Participants", "Group", "Dependent variable", "Range of group-low", "Range of group-high"), 
       fill = c("lightblue", "pink", "lightgreen", "lightyellow", "lavender"), cex=0.8)
```
Hypothesis 1

```{r}

# Split data by Group
split_data <- split(data$`Dependent variable`, data$Group)

# Conduct t-tests for each group
for (i in 1:length(split_data)) {
  group <- names(split_data[i])
  results <- t.test(split_data[[i]])
  print(paste0("Group ", group, ": t = ", results$statistic, ", p-value = ", results$p.value))
}

```

hypotheis 2
```{r}
# Fit a linear regression model
model <- lm(`Dependent variable` ~ `Range of group-high`, data = data)

# Get the summary of the model
summary(model)

```