You are analyzing a set of data that includes the following variables: - event_ID: used to label each event - data_type: the type of data breached - num_people {in millions]: the number of people impacted by a data breach. expressed in millions - num_people_v2: coded version of the variable num_people - per_sensitive: percent of sensitive data breached - dys_impact: the length of the negative nancial impact from the data breach A subset of this data is shown in the image below: event_l9I data_type 'lihmnli'lli::ri}e num_people_v2 per_sensitive dys_impact 1 Intellectual Property 51.?1 Between 39 to 99 million 19 1141 2 Intellectual Property 51.93 Between 39 to 99 million 19 191? 3 Identity 59.49 Between 39 to 99 million 29 999 4. Personal 41.91 Between 39 to 99 million 95_ 192? 5 Personal 59.32 Between 39 to 99 million 4 ?94 9 Personal 49.91 Between 39 to 99 million 39 1599 ? Intellectual Property 92.?9 More than 99 million 199 1599 BIAutl-ienticaon Credentials 35.36 Between 39 to 99 million 23 1499 9 Financial 49.99 Between 39 to 99 million 95 295 19. Health 43.91 Between 39 to 99 million 13 149? 11 Intellectual Property 91.19 More than 99 million 199 3?4 12 Identity 44.94 Between 39 to 99 million 99 999 13 Health 91.95 More than 99 million 4? 42 14_ Financial 55.91 Between 39 to 99 million 23 519 15 Authentication Credentials 45.2? Between 39 to 99 million 49 ?99 19 Personal 59.51 Between 39 to 99 million 58 1?59 1? Identity 59.99 Between 39 to 99 million 98 232 13 Intellectual Property 59.?9 Between 39 to 99 million 4_ 1395 19 Financial 44.92 Between 39 to 99 million 48 125? 29 Health ?2.93 More than 99 million 99 199