Analysing global professional gender gaps using LinkedIn advertising data

EPJ Data Science

Table 2 Summary statistics of LinkedIn Gender Gap Indices (GGI) by different characteristics (as displayed in Fig. 2)

Category	Min.	1st quartile (25% percentile)	Median (50% percentile)	3rd quartile (75% percentile)	Max.	Number of countries
Overall	0.13	0.51	0.73	0.89	2.12	234
Age group
18–24	0.13	0.57	0.88	1.10	2.09	187
25–34	0.14	0.55	0.89	1.04	2.60	201
35–54	0.00	0.42	0.63	0.79	1.82	194
55+	0.00	0.27	0.38	0.53	1.93	133
Company industry
Non-STEM	0.00	0.41	0.74	0.97	4.33	190
STEM	0.00	0.22	0.41	0.54	1.56	164
Field of study
Non-STEM	0.08	0.57	0.88	1.15	4.31	175
STEM	0.00	0.16	0.24	0.36	1.64	147
Job function
Non-STEM	0.00	0.50	0.86	1.06	2.98	203
STEM	0.00	0.25	0.37	0.48	1.36	201
Job seniority
Chief X Officer (CxO)	0.00	0.24	0.33	0.40	0.74	137
Director	0.00	0.34	0.50	0.63	1.56	177
Entry-level	0.13	0.50	0.79	0.95	1.92	218
Manager	0.00	0.38	0.52	0.68	1.97	184
Owner	0.00	0.29	0.41	0.52	1.08	153
Partner	0.00	0.32	0.39	0.48	3.55	87
Senior	0.14	0.50	0.79	1.00	2.67	212
Training	0.00	0.65	0.92	1.07	2.30	126
Unpaid	0.25	0.55	0.66	0.79	1.39	98
Vice President (VP)	0.00	0.25	0.36	0.58	1.37	140