IBM SPSS COMPLEX SAMPLES 19 manual Sample Files

259

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. This is a hypothetical data file containing financial and demographic information on 5,000 past customers.

„behavior.sav. In a classic example (Price and Bouffard, 1974), 52 students were asked to rate the combinations of 15 situations and 15 behaviors on a 10-point scale ranging from 0=“extremely appropriate” to 9=“extremely inappropriate.” Averaged over individuals, the values are taken as dissimilarities.

„behavior_ini.sav. This data file contains an initial configuration for a two-dimensional solution for behavior.sav.

„brakes.sav. This is 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 discs from each of 8 production machines. The target diameter for the brakes is 322 millimeters.

„breakfast.sav. In a 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 were recorded under six different scenarios, from “Overall preference” to “Snack, with beverage only.”

„breakfast-overall.sav.This data file contains the breakfast item preferences for the first scenario, “Overall preference,” only.

„broadband_1.sav. This is a hypothetical data file containing the number of subscribers, by region, to a national broadband service. The data file contains monthly subscriber numbers for 85 regions over a four-year period.

„broadband_2.sav. This data 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 variable to a linear combination of the policyholder age, vehicle type, and vehicle age. The number of claims filed can be used as a scaling weight.

„car_sales.sav. This data file contains hypothetical sales estimates, list prices, and physical specifications for various makes and models of vehicles. The list prices and physical specifications were obtained alternately from edmunds.com and manufacturer sites.

„car_sales_uprepared.sav. This is 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 cleaner wants 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 differing in the location of the applicator brush; three brand names (K2R, Glory, and Bissell); three price levels; and two levels (either no or 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.