age job marital education default balance housing loan contact day month duration campaign pdays previous poutcome y

$58$ management married tertiary no $2143$ yes no unknown $5$ may $2611-10$ unknown no

$44$ technician single secondary no $29$ yes no unknown $5$ may $1511-10$ unknown no

$33$ entrepreneur married secondary no $2$ yes yes unknown $5$ may $761-10$ unknown no

$47$ blue$-$collar married unknown no $1506$ yes no unknown $5$ may $921-10$ unknown no

$33$ unknown single unknown no $1$ no no unknown $5$ may $1981-10$ unknown no

$35$ management married tertiary no $231$ yes no unknown $5$ may $1391-10$ unknown no

$28$ management single tertiary no $447$ yes yes unknown $5$ may $2171-10$ unknown no

$42$ entrepreneur divorced tertiary yes $2$ yes no unknown $5$ may $3801-10$ unknown no

$58$ retired married primary no $121$ yes no unknown $5$ may $501-10$ unknown no

$43$ technician single secondary no $593$ yes no unknown $5$ may $551-10$ unknown no

$41$ admin. divorced secondary no $270$ yes no unknown $5$ may $2221-10$ unknown no

$29$ admin. single secondary no $390$ yes no unknown $5$ may $1371-10$ unknown no

$53$ technician married secondary no $6$ yes no unknown $5$ may $5171-10$ unknown no

$58$ technician married unknown no $71$ yes no unknown $5$ may $711-10$ unknown no

$57$ services married secondary no $162$ yes no unknown $5$ may $1741-10$ unknown no

$51$ retired married primary no $229$ yes no unknown $5$ may $3531-10$ unknown no

$45$ admin. single unknown no $13$ yes no unknown $5$ may $981-10$ unknown no

$57$ blue$-$collar married primary no $52$ yes no unknown $5$ may $381-10$ unknown no

$60$ retired married primary no $60$ yes no unknown $5$ may $2191-10$ unknown no

$33$ services married secondary no $0$ yes no unknown $5$ may $541-10$ unknown no

$28$ blue$-$collar married secondary no $723$ yes yes unknown $5$ may $2621-10$ unknown no

$56$ management married tertiary no $779$ yes no unknown $5$ may $1641-10$ unknown no

$32$ blue$-$collar single primary no $23$ yes yes unknown $5$ may $1601-10$ unknown no

$25$ services married secondary no $50$ yes no unknown $5$ may $3421-10$ unknown no

$40$ retired married primary no $0$ yes yes unknown $5$ may $1811-10$ unknown no

$44$ admin. married secondary no $-372$ yes no unknown $5$ may $1721-10$ unknown no

$39$ management single tertiary no $255$ yes no unknown $5$ may $2961-10$ unknown no

$52$ entrepreneur married secondary no $113$ yes yes unknown $5$ may $1271-10$ unknown no

$46$ management single secondary no $-246$ yes no unknown $5$ may $2552-10$ unknown no

$36$ technician single secondary no $265$ yes yes unknown $5$ may $3481-10$ unknown no

$57$ technician married secondary no $839$ no yes unknown $5$ may $2251-10$ unknown no

$49$ management married tertiary no $378$ yes no unknown $5$ may $2301-10$ unknown no

$60$ admin. married secondary no $39$ yes yes unknown $5$ may $2081-10$ unknown no

$59$ blue$-$collar married secondary no $0$ yes no unknown $5$ may $2261-10$ unknown no

$51$ management married tertiary no $10635$ yes no unknown $5$ may $3361-10$ unknown no

$57$ technician divorced secondary no $63$ yes no unknown $5$ may $2421-10$ unknown no

$25$ blue$-$collar married secondary no $-7$ yes no unknown $5$ may $3651-10$ unknown no

$53$ technician married secondary no $-3$ no no unknown $5$ may $16661-10$ unknown no

$36$ admin. divorced secondary no $506$ yes no unknown $5$ may $5771-10$ unknown no

$37$ admin. single secondary no $0$ yes no unknown $5$ may $1371-10$ unknown no

$44$ services divorced secondary no $2586$ yes no unknown $5$ may $1601-10$ unknown no

$50$ management married secondary no $49$ yes no unknown $5$ may $1802-10$ unknown no

$60$ blue$-$collar married unknown no $104$ yes no unknown $5$ may $221-10$ unknown no

$54$ retired married secondary no $529$ yes no unknown $5$ may $14921-10$ unknown no

$58$ retired married unknown no $96$ yes no unknown $5$ may $6161-10$ unknown no

$36$ admin. single primary no $-171$ yes no unknown $5$ may $2421-10$ unknown no

$58$ self$-$employed married tertiary no $-364$ yes no unknown $5$ may $3551-10$ unknown no

$44$ technician married secondary no $0$ yes no unknown $5$ may $2252-10$ unknown no

$55$ technician divorced secondary no $0$ no no unknown $5$ may $1601-10$ unknown no

$29$ management single tertiary no $0$ yes no unknown $5$ may $3631-10$ unknown no

$54$ blue$-$collar married secondary no $1291$ yes no unknown $5$ may $2661-10$ unknown no

$48$ management divorced tertiary no $-244$ yes no unknown $5$ may $2531-10$ unknown no

$32$ management married tertiary no $0$ yes no unknown $5$ may $1791-10$ unknown no

$42$ admin. single secondary no $-76$ yes no unknown $5$ may $7871-10$ unknown no

$24$ technician single secondary no $-103$ yes yes unknown $5$ mThe data set below contains data on direct marketing campaigns of a banking institution. Clients were contacted by phone with the goal of having them subscribe to a term deposit $($that is$,$ open a certificate of deposit $($CD$)$ account$).$

Bank data.xlsx

$($Note: The file may not open when using Microsoft Edge. Use another browser or right$-$click "Save link as$"$ to download the data file.$)$

This data set is an example of

a$.$

cross$-$sectional data.

b$.$

time$-$series data.

c$.$

panel data.

d$.$

aggregate data.