Load Data

data <- read_excel("C:/Users/MFLAB/Desktop/Econ 465/Data/Incites Researchers.xlsx")
names(data)
##  [1] "percent" "wos"     "cnci"    "rank"    "cites"   "aff1"    "aff2"   
##  [8] "aff3"    "aff4"    "aff5"    "aff6"    "aff7"    "aff8"    "aff9"   
## [15] "aff10"   "id"      "impact"  "ORCID"   "...19"   "...20"   "...21"  
## [22] "...22"   "...23"   "...24"   "...25"   "...26"   "...27"   "...28"  
## [29] "...29"   "...30"   "...31"

Filter Data

ieu_data <- data |> 
  filter(aff1 == "İzmir Ekonomi Üniversitesi")
ieu_data
## # A tibble: 0 × 31
## # ℹ 31 variables: percent <dbl>, wos <dbl>, cnci <dbl>, rank <dbl>,
## #   cites <dbl>, aff1 <chr>, aff2 <chr>, aff3 <chr>, aff4 <chr>, aff5 <chr>,
## #   aff6 <chr>, aff7 <chr>, aff8 <chr>, aff9 <chr>, aff10 <chr>, id <chr>,
## #   impact <dbl>, ORCID <chr>, ...19 <lgl>, ...20 <chr>, ...21 <chr>,
## #   ...22 <chr>, ...23 <chr>, ...24 <chr>, ...25 <chr>, ...26 <chr>,
## #   ...27 <chr>, ...28 <chr>, ...29 <chr>, ...30 <chr>, ...31 <chr>

Histogram of Impact

ggplot(ieu_data, aes(x = impact)) +
  geom_histogram(binwidth = 1, color = "black", fill = "steelblue") +
  labs(
    title = "Histogram of Researcher Impact",
    x = "Impact",
    y = "Frequency"
  ) +
  theme_minimal()

Boxplot of Impact

ggplot(ieu_data, aes(y = impact)) +
  geom_boxplot(fill = "orange") +
  labs(
    title = "Boxplot of Researcher Impact",
    y = "Impact"
  ) +
  theme_minimal()

Interpretation

The distribution of impact is right-skewed. Most researchers have relatively low impact values, while a smaller number have much higher values. The center is in the lower-to-middle range, the spread is fairly wide, and the boxplot suggests the presence of outliers. This shows that research impact is unevenly distributed across researchers.