| Title: | Data Sets for Keith McNulty's Handbook of Regression Modeling in People Analytics |
| Version: | 0.2.1 |
| Description: | Data sets for statistical inference modeling related to People Analytics. Contains various data sets from the book 'Handbook of Regression Modeling in People Analytics' by Keith McNulty (2020). |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| URL: | http://peopleanalytics-regression-book.org |
| RoxygenNote: | 7.1.1 |
| Depends: | R (≥ 2.10) |
| NeedsCompilation: | no |
| Packaged: | 2021-04-13 09:44:53 UTC; rstudio |
| Author: | Keith McNulty 
[aut, cre] |
| Maintainer: | Keith McNulty <keith.mcnulty@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2021-04-13 10:00:02 UTC |
Charity donation data
Description
Fictional data on the demographics and donation behavior of donors to a wildlife charity
Usage
charity_donation
Format
A dataframe with 354 rows and 8 variables:
- n_donations
The total number of times the individual donated previous to the month being studied
- total_donations
The total amount of money donated by the individual previous to the month being studied
- time_donating
The number of months between the first donation and the month being studied
- recent_donation
Whether or not the individual donated in the month being studied
- last_donation
The number of months between the most recent previous donation and the month beng studied
- gender
The gender of the individual
- reside
Whether the person resides in an Urban or Rural Domestic location or Overseas
- age
The age of the individual
Examples
charity_donation
Employee performance data
Description
Fictional data on employee performance evaluation metrics for a group of salespeople.
Usage
employee_performance
Format
A dataframe with 366 rows and 5 variables:
- sales
The annual sales of the individual in millions of dollars
- new_customers
The number of new customers acquired by the individual
- region
The region the individuals works in - North, South, East or West
- gender
The gender of the individual
- rating
The performance rating of the individual - 1 = Low, 2 = Middle, 3 = High
Examples
employee_performance
Employee survey data
Description
Fictional data on the results of an engagement survey among company employees on a four-point Likert scale indicating increasingly positive sentiment
Usage
employee_survey
Format
A dataframe with 2833 rows and 14 variables:
- Happiness
The employee rating on their overall happiness
- Ben1, Ben2, Ben3
The employee rating on three questions related to employment benefits
- Work1, Work2, Work3
The employee rating on three questions related to general work environment
- Man1, Man2, Man3
The employee rating on three questions related to perceptions of management
- Car1, Car2, Car3, Car4
The employee rating on four questions related to perceptions of career prospects
Examples
employee_survey
Graduate salary data
Description
Data on graduate salaries in the United States
Usage
graduates
Format
A dataframe with 173 rows and 5 variables:
- Major
The specific subject major
- Discipline
The broad subject discipline
- Total
The number of graduates of working age in the US
- Unemployment_rate
The proportion of graduates currently unemployed
- Median_salary
The current median salary of those employed in US dollars
Source
Examples
graduates
Health insurance data
Description
Fictional data on the choice of health insurance product by employees of a large company
Usage
health_insurance
Format
A dataframe with 1453 rows and 6 variables:
- product
The choice of product of the individual - A, B or C
- age
The age of the individual when they made the choice
- household
The number of people living with the individual in the same household at the time of the choice
- position_level
The individual's position level in the company at the time they made the choice, where 1 is is the lowest and 5 is the highest
- gender
The gender of the individual as stated when they made the choice
- absent
The number of days the individual was absent from work in the year prior to the choice
Examples
health_insurance
Job retention data
Description
Fictional data on the retention of employees in various fields of employment over a 12 month period
Usage
job_retention
Format
A dataframe with 3770 rows and 7 variables:
- gender
The gender of the individual studied
- field
The field of employment of the individual at the beginning of the study
- level
The level of the position of the individual in their organization at the beginning of the study - Low, Medium or High
- sentiment
The sentiment score reported by the individual on a scale of 1 to 10 at the beginning of the study, with 1 indicating extremely negative sentiment and 10 indicating extremely positive sentiment
- intention
A score of 1 to 10 reported by the individual at the beginning of the study regarding their intention to leave their job in the next 12 months, where 1 indicates an extremely low intention and 10 indicates an extremely high intention
- left
A binary variable indicating whether or not the individual had left their job as at the last follow-up
- month
The month of the last follow-up
Examples
job_retention
Learning program feedback data
Description
Fictional data on feedback from participants in a set of learning programs
Usage
learning
Format
A dataframe with 4974 rows and 8 variables:
- idcode
The unique ID code of the participant
- rec
A binary value indicating whether the participant would recommend the program to others
- rel
A rating from the participant on the relevance of the program to their work, where 1 is Very Low and 5 is Very High
- fun
A rating on how enjoyable and fun the participant found the program, where 1 is Very Low and 5 is Very High
- clar
A rating from the participant on the clarity of the content and teaching in the program, where 1 is Very Low and 5 is Very High
- home
A rating from the participant on the quality of the homework or project work in the program, where 1 is Very Low and 5 is Very High
- class
A rating from the participant on the quality of the overall class who attended the program, where 1 is Very Low and 5 is Very High
- fac
A rating from the participant on the quality of the program faculty and instructors, where 1 is Very Low and 5 is Very High
Examples
learning
Manager performance data
Description
Fictional data on the performance and other characteristics of a group of managers in a large company
Usage
managers
Format
A dataframe with 571 rows and 13 variables:
- employee_id
The unique ID number for each manager
- performance_group
The performance group of each manager in a recent performance review: Bottom performer, Middle performer, Top performer
- yrs_employed
Total length of time employed by the company in years
- manager_hire
Whether or not the individual was hired directly to be a manager (Y) or promoted to manager (N)
- test_score
Score on a test given to all managers
- group_size
The number of employees in the group the manager is responsible for
- concern_flag
Whether or not the individual has been the subject of a complaint by a member of their group
- mobile_flag
Whether or not the individual works mobile (Y) or in the office (N)
- customers
The number of customer accounts the manager is responsible for
- high_hours_flag
Whether or not the manager has entered unusually high hours into their timesheet in the past year
- transfers
The number of transfer requests coming from the manager’s group while they have been a manager
- reduced_schedule
Whether the manager works part time (Y) or full time (N)
- city
The current office of the manager
Examples
managers
Politics survey data
Description
Fictional data from a survey conducted by a political party on a Likert scale of 1 to 4 indicating increasingly positive sentiment
Usage
politics_survey
Format
A dataframe with 2108 rows and 23 variables:
- Overall
The respondent's overall intention to vote for the party in the next election
- Pol1, Pol2, Pol3
The respondent's sentiment on three questions related to the policies of the party
- Hab1, Hab2, Hab3
The respondent's sentiment on three questions regarding prior voting habits in relation to the party
- Loc1, Loc2, Loc3, Loc4
The respondent's sentiment on four questions related to their interest in local issues
- Env1, Env2
The respondent's sentiment on two questions related to their interest in environment issues
- Int1, Int2
The respondent's sentiment on two questions related to their interest in international issues
- Pers1, Pers2, Pers3
The respondent's sentiment on three questions related to their perceptions of the personalities of local and national party leaders
- Nat1, Nat2, Nat3
The respondent's sentiment on three questions related to their interest in national issues
- Eco1, Eco2
The respondent's sentiment on two questions related to their interest in economic issues
Examples
politics_survey
Promotion data
Description
Fictional data on promotions in a retail company
Usage
promotion
Format
A dataframe with 1134 rows and 5 variables:
- diverse
A binary value indicating membership of a diversity group at the company
- flexible
A binary value indicating whether or not the individual worked part-time for at least 6 months
- store
A binary value indicating whether the individual joined in a position working in the retail stores
- promoted
A binary value indicating whether or not the individual was promoted
- result
The year of the last record of the individual, where the date they joined was year 0. If the individual was promoted, this will be the year of the promotion.
Examples
promotion
Recruiting data
Description
Fictional data on applicants to a graduate recruiting program in a financial services company
Usage
recruiting
Format
A dataframe with 966 rows and 8 variables:
- gender
The gender of the applicant
- sat
The SAT score of the applicant
- gpa
The GPA of the applicant
- apttest
The result of an aptitude test given to the applicant
- int1, int2
Applicant rating given by two line manager interviewers, on a Likert Scale of 1 to 5 indicating increasing positivity
- int3
Applicant rating given by a human resources interviewer, on a Likert Scale of 1 to 5 indicating increasing positivity
- hired
Binary indicating whether the decision was Hire (1) or No Hire (0)
Examples
recruiting
Salespeople promotion data
Description
Fictional data on promotion and performance for salespeople in a technology company
Usage
salespeople
Format
A dataframe with 351 rows and 4 variables:
- promoted
A binary value indicating 1 if the individual was promoted and 0 if not
- sales
The sales (in thousands of dollars) attributed to the individual in the period of the promotion
- customer_rate
The average satisfaction rating from a survey of the individual’s customers during the promotion period
- performance
The most recent performance rating prior to promotion from 1 (lowest) to 4 (highest)
Examples
salespeople
Soccer discipline data
Description
Fictional data on disciplinary measures by referees in soccer games
Usage
soccer
Format
A dataframe with 2291 rows and 7 variables:
- discipline
A record of the maximum discipline taken by the referee against the player in the game. “None” means no discipline was taken, “Yellow” means the player was issued a yellow card (warned), “Red” means the player was issued a red card and ordered off the field of play
- n_yellow_25
The total number of yellow cards issued to the player in the previous 25 games they played prior to this game
- n_red_25
The total number of red cards issued to the player in the previous 25 games they played prior to this game
- position
The playing position of the player in the game: “D” is defence (including goalkeeper), “M” is midfield and “S” is striker/attacker
- result
The result of the game for the team of the player - “W” is win, “L” is lose, “D” is a draw/tie
- country
The country in which the game took place - England or Germany
- level
The skill level of the competition in which the game took place, with 1 being higher and 2 being lower
Examples
soccer
Sociological survey data
Description
Fictional data on a sociological survey related to income levels in various regions of the world.
Usage
sociological_data
Format
A dataframe with 2618 rows and 9 variables:
- annual_income_ppp
The annual income of the individual in PPP adjusted US dollars
- average_wk_hrs
The average number of hours per week worked by the individual
- education_months
The total number of months spend by the individual in formal primary, secondary and tertiary education
- region
The region of the world where the individual lives
- job_type
Whether the individual works in a skilled or unskilled profession
- gender
The gender of the individual
- family_size
The size of the individual’s family of dependents
- work_distance
The distance between the indivdual’s residence and workplace in kilometers
- languages
The number of languages spoken fluently by the individual
Examples
sociological_data
Speed dating data
Description
Simplified version of the Columbia University speed dating experiment data set
Usage
speed_dating
Format
A dataframe with 8378 rows and 11 variables:
- iid
An id number for the individual
- gender
The gender of the individual with 0 as Female and 1 and Male
- match
Indicates if the meeting resulted in a match
- samerace
Indicates if both the individual and the partner were of the same race
- race
The race of the individual, with race coded as follows: Black/African American=1, European/Caucasian-American=2, Latino/Hispanic American=3, Asian/Pacific Islander/Asian-American=4, Native American=5, Other=6
- goal
The reason why the individual is participating in the event, coded as follows: Seemed like a fun night out=1, To meet new people=2, To get a date=3, Looking for a serious relationship=4, To say I did it=5, Other=6
- dec
A binary rating from the individual as to whether they would like to see their partner again (1 is Yes and 0 is No)
- attr
The individual’s rating out of ten on the attractiveness of the partner
- intel
The individual’s rating out of ten on the intelligence level of the partner
- prob
The individual’s rating out of ten on whether they believe the partner will want to see them again
- agediff
The absolute difference in the ages of the individual and the partner
Source
Examples
speed_dating
Undergraduate examination data
Description
Fictional data on examination scores of undergraduates on a four year biology degree program.
Usage
ugtests
Format
A dataframe with 975 rows and 4 variables:
- Yr1
Score in the first year examination on a scale of 0-100
- Yr2
Score in the second year examination on a scale of 0-200
- Yr3
Score in the third year examination on a scale of 0-200
- Final
Score in the final year examination on a scale of 0-300
Examples
ugtests