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Sample Files
loans. The last 150 cases are prospective customers that the bank needs to classify as good
or bad credit risks.
bankloan_binning.sav. Thisis a hypothetical data file containing financial and demographic
information on 5,000 past customers.
behavior.sav. Ina classic example (Price and Bouffard, 1974), 52 st udents were asked to
rate the combinations of 15 situationsand 15 behaviors on a 10-point scale ranging from
0=“extremely appropriate” to9=“extremely inappropriate.” Averaged over individuals, the
values are taken as dissimilarities.
behavior_ini.sav. Thisdata file contains an initial configuration for a two-d imensional solution
for behavior.sav.
brakes.sav. Thisis a hypothetical data file that concerns quality control at a factory that
produces disc brakes for high-performance automobiles. The data file contains diameter
measurements of 16 discsfrom each of 8 production machines. The target diameter for the
brakes is 322 millimeters.
breakfast.sav. Ina classic study (Green and Rao, 1972), 21 Wharton School MBA students
and their spouses were asked to rank 15 breakfast items in order of preference with 1=“most
preferred” to 15=“least preferred.” Their preferences wererecorded under six different
scenarios, from “Overall preference” to “Snack, with beverageonly.”
breakfast-overall.sav. This data file contains the breakfast item preferences for the first
scenario, “Overall preference,” only.
broadband_1.sav. Thisis a hypothetical data file containing the number of subscribers, by
region, to a national broadbandservice. The data file contains monthly subscriber numbers
for 85 regions over a four-yearperiod.
broadband_2.sav. Thisdata file is identical to broadband_1.sav but contains data for three
additional months.
car_insurance_claims.sav. A dataset presented and analyzed elsewhere (McCullagh and
Nelder,1989) concerns damage claims for cars. The average claim amount can be modeled
as having a gamma distribution,using an inverse link function to relate the mean of the
dependent variableto a linear combination of the policyholder age, vehicle type, and vehicle
age.Thenumberofclaimsfiledcan be used as a scaling weight.
car_sales.sav. This data file contains hypothetical salesestimates, list prices, and physical
specifications for various makes and models of vehicles. The list prices and physical
specificationswere obtainedalternately from edmunds.com and manufacturer sites.
car_sales_uprepared.sav. Thisis a modified version of car_sales.sav that does not include any
transformed versions of the fields.
carpet.sav. In a popular example (Green and Wind, 1973),a company interested in
marketing a new carpet cleanerwants to examine the influence of five factors on consumer
preference—package design, brand name, price, a Good Housekeeping seal, and a
money-back guarantee. There are three factor levels for package design, each one differingin
the location of theapplicator brush; three brand names (K2R,Glory,andBissell);three price
levels; and two levels (either noor yes) for each of the last two factors. Ten consumers rank
22 profiles defined by these factors. The variable Preference contains the rank of the average
rankings for each profile. Low rankings correspond to high preference. This variable reflects
an overall measure of preference for each profile.