Correction - Insert Research Question: Is there a difference in mean body weight (kg) between participants who do cardio versus participants who do not do cardio?

Open Packages.

library(dplyr)
library(effectsize)
library(effsize)
library(readxl)
library(ggpubr)
library(ggplot2)
library(rstatix)

Import data set.

A6Q3_2 <- read_excel("C:/Users/rmich/Desktop/A6Q3-2.xlsx")

Descriptive statistics.

A6Q3_2 %>%
  group_by(Exercise) %>%
  summarise(
    Mean = mean(Weight, na.rm = TRUE),
    Median = median(Weight, na.rm = TRUE),
    SD = sd(Weight, na.rm = TRUE),
    N = n()
  )
## # A tibble: 2 × 5
##   Exercise  Mean Median    SD     N
##   <chr>    <dbl>  <dbl> <dbl> <int>
## 1 cardio    74.7   73.3  7.57    25
## 2 nocardio  70.8   69.5  7.35    25

Create histogram.

hist(A6Q3_2$Weight[A6Q3_2 == "cardio"],
     main = "Body Weight Distribution: Cardio",
     xlab = "Weight",
     ylab = "Count",
     col = "lightblue",
     border = "black",
     breaks = 10)

hist(A6Q3_2$Weight[A6Q3_2 == "nocardio"],
     main = "Body Weight Distribution: No Cardio",
     xlab = "Weight",
     ylab = "Count",
     col = "lightgreen",
     border = "black",
     breaks = 10)

Group 1: Body Weight Distribution: Cardio The first variable looks normally distributed. The data is negatively skewed. Correction: Data is symetrical. Student error. The data does have a proper bell curve.

Group 2: Body Weight Distribution: No Cardio The second variable looks normally distributed. The data is negatively skewed. Correction: Data is symetrical. Student error. The data does have a proper bell curve.

ggboxplot(
  A6Q3_2,
  x = "Exercise",
  y = "Weight",
  color = "Exercise",
  palette = "jco",
  add = "jitter"
)

Create boxplots. Boxplot 1: No Cardio There are no dots outside the boxplot. Correction: There are dots. Student error. Review boxplot definition. The dots are close to the whiskers. The dots are not very far away from the whiskers. The outliers are balanced. Based on these findings, the boxplot is normal.

Boxplot 2: Cardio There are no dots outside the boxplot. Correction: There are dots. Student error. Review boxplot definition. The dots are close to the whiskers. The dots are not very far away from the whiskers. The outliers are balanced. Based on these findings, the boxplot is normal.

Check normality.

shapiro.test(A6Q3_2$Weight[A6Q3_2$Exercise == "cardio"])
## 
##  Shapiro-Wilk normality test
## 
## data:  A6Q3_2$Weight[A6Q3_2$Exercise == "cardio"]
## W = 0.96745, p-value = 0.5812
shapiro.test(A6Q3_2$Weight[A6Q3_2$Exercise == "nocardio"])
## 
##  Shapiro-Wilk normality test
## 
## data:  A6Q3_2$Weight[A6Q3_2$Exercise == "nocardio"]
## W = 0.97686, p-value = 0.8166

Group 1: Cardio The first group is normally distributed, (p = .817). Correction - rounding error. Modify from .817 to . 82.

Group 2: No Cardio The second group is normally distributed, (p = .581). Correction - rounding error. Modify from .581 to .59

t.test(Weight ~ Exercise, data = A6Q3_2, var.equal = TRUE)
## 
##  Two Sample t-test
## 
## data:  Weight by Exercise
## t = 1.8552, df = 48, p-value = 0.06971
## alternative hypothesis: true difference in means between group cardio and group nocardio is not equal to 0
## 95 percent confidence interval:
##  -0.3280454  8.1605622
## sample estimates:
##   mean in group cardio mean in group nocardio 
##               74.73336               70.81710

t.test(Weight ~ Exercise, data = A6Q3_2, var.equal = TRUE)

Correction: Remove Wilcox, remove Cohens D.

An Independent T-Test was conducted to determine if there was a difference in Weight between those who exercise and those who did not exercise. Those who exercised weighed (M = 74.7, SD = 7.57) were not significantly different from those who did not (M = 70.8, SD = 7.35), t(48) = 1.86, p > .05. Correction: Modify p > .05. not specific number.