DataDiveWeek2

Summary of Daily Social Media Time (hrs) and Monthly Income (USD)

Load the data

data <-read.csv("social_media_entertainment_data.csv")

Numeric summaries

Social_Media_Summary <- data %>% 
  summarise( 
    Min = min(Daily.Social.Media.Time..hrs.), 
    Max = max(Daily.Social.Media.Time..hrs.), 
    Mean = mean(Daily.Social.Media.Time..hrs.), 
    Median = median(Daily.Social.Media.Time..hrs.), 
    Q1 = quantile(Daily.Social.Media.Time..hrs., 0.25), 
    Q3 = quantile(Daily.Social.Media.Time..hrs., 0.75) 
    )

Income_Summary <- data %>% 
  summarise( 
    Min = min(Monthly.Income..USD.), 
    Max = max(Monthly.Income..USD.), 
    Mean = mean(Monthly.Income..USD.), 
    Median = median(Monthly.Income..USD.), 
    Q1 = quantile(Monthly.Income..USD., 0.25), 
    Q3 = quantile(Monthly.Income..USD., 0.75)
    )

list(SocialMedia = Social_Media_Summary, Income = Income_Summary)

## $SocialMedia
##   Min Max     Mean Median   Q1   Q3
## 1 0.5   8 4.254808   4.26 2.38 6.13
## 
## $Income
##      Min     Max     Mean  Median       Q1       Q3
## 1 500.01 9999.93 5256.919 5259.01 2883.818 7630.525

Gathered Info

Daily Social Media Time (hrs):

• The minimum time spent on social media is 0.5 hours, while the maximum is 8 hours.

• The mean time spent is around 4.25 hours with a median of 4.26 hours.

• Observation: Based on the IQR, most users fall within the 2-6 hour range, suggesting social media is a regular part of their routine.

Monthly Income (USD):

• Monthly income ranges from $500.01 to $9,999.93

• The mean income is $5,256.92, with a median of $5,259.01

• Observation: There is a large variation in income, but the data clusters around the $5,000 range.

Investigative Questions

1. How does daily social media time vary across different primary platforms?

2. Does monthly income vary significantly between different occupations?

3. Is there a correlation between internet speed and time spent in online communities?

Average_Time_By_Platform <- data %>% 

  group_by(Primary.Platform) %>% 

  summarise(AverageTime = mean(Daily.Social.Media.Time..hrs.))

Average_Time_By_Platform

## # A tibble: 5 × 2
##   Primary.Platform AverageTime
##   <chr>                  <dbl>
## 1 Facebook                4.26
## 2 Instagram               4.25
## 3 TikTok                  4.25
## 4 Twitter                 4.25
## 5 YouTube                 4.27

Analysis:

• The data suggests that users split their time evenly across different platforms

• Equal distribution of time could indicate that no single platform dominates users’ daily routines

data_summary <- data %>%
  group_by(Country, Internet.Speed..Mbps.) %>%
  summarise(AverageTime = mean(Daily.Social.Media.Time..hrs., na.rm = TRUE)) %>%
  ungroup() %>%
  arrange(Country, Internet.Speed..Mbps.)

## `summarise()` has grouped output by 'Country'. You can override using the
## `.groups` argument.

ggplot(data_summary, aes(x = Internet.Speed..Mbps., y = AverageTime, color = Country, group = Country)) +
  geom_line() + geom_point(alpha = 0.5) +
  labs(
    title = "Social Media Consumption vs Internet Speed by Country",
    x = "Internet Speed (Mbps)",
    y = "Average Social Media Time (hrs)"
  )

Insights:

• There are similar patterns across all countries, showing that the internet speed does not have as much effect on the time.

• USA dominates the plot keeping a steady rate of social media time.

# Create age ranges
data <- data %>%
  mutate(AgeRange = cut(Age, 
                        breaks = c(0, 18, 25, 35, 45, 55, 65, 100),
                        labels = c("0-18", "18-25", "26-35", "36-45", "46-55", "56-65", "65+")))

age_social_media <- data %>%
  group_by(AgeRange) %>%
  summarise(AverageTime = mean(Daily.Social.Media.Time..hrs., na.rm = TRUE))

ggplot(data, aes(x = AgeRange, y = Daily.Social.Media.Time..hrs.)) +
  geom_boxplot(fill = "lightblue", color = "black") +
  facet_wrap(~ Country) +
  labs(title = "Social Media Consumption Across Age Ranges by Country",
       x = "Age Range", 
       y = "Daily Social Media Time (hrs)") +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

Insights:

• The data suggests that each country has similar social media consumption time by age range.

• The overall average time spent on social media is approximately 4 hours per day, which remains relatively constant between countries.

• The data suggests that age ranges or country specific factors don’t drastically influence the overall time spent