Sample Files

The sample files installed with the product can be found in the Samples subdirectory of the installation directory. There is a separate folder within the Samples subdirectory for each of the following languages: English, French, German, Italian, Japanese, Korean, Polish, Russian, Simplified Chinese, Spanish, and Traditional Chinese.

Not all sample files are available in all languages. If a sample file is not available in a language, that language folder contains an English version of the sample file.

Descriptions

Following are brief descriptions of the sample files used in various examples throughout the documentation.

• accidents.sav. This is a hypothetical data file that concerns an insurance company that is studying age and gender risk factors for automobile accidents in a given region. Each case corresponds to a cross-classification of age category and gender.
• adl.sav. This is a hypothetical data file that concerns efforts to determine the benefits of a proposed type of therapy for stroke patients. Physicians randomly assigned female stroke patients to one of two groups. The first received the standard physical therapy, and the second received an additional emotional therapy. Three months following the treatments, each patient's abilities to perform common activities of daily life were scored as ordinal variables.
• advert.sav. This is a hypothetical data file that concerns a retailer's efforts to examine the relationship between money spent on advertising and the resulting sales. To this end, they have collected past sales figures and the associated advertising costs.
• aflatoxin.sav. This is a hypothetical data file that concerns the testing of corn crops for aflatoxin, a poison whose concentration varies widely between and within crop yields. A grain processor has received 16 samples from each of 8 crop yields and measured the alfatoxin levels in parts per billion (PPB).
• anorectic.sav. While working toward a standardized symptomatology of anorectic/bulimic behavior, researchers ¹ made a study of 55 adolescents with known eating disorders. Each patient was seen four times over four years, for a total of 220 observations. At each observation, the patients were scored for each of 16 symptoms. Symptom scores are missing for patient 71 at time 2, patient 76 at time 2, and patient 47 at time 3, leaving 217 valid observations.
• bankloan.sav. This is a hypothetical data file that concerns a bank's efforts to reduce the rate of loan defaults. The file contains financial and demographic information on 850 past and prospective customers. The first 700 cases are customers who were previously given 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 ², 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 ³, 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 ⁴ 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 ⁵, 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.
• carpet_prefs.sav. This data file is based on the same example as described for carpet.sav, but it contains the actual rankings collected from each of the 10 consumers. The consumers were asked to rank the 22 product profiles from the most to the least preferred. The variables PREF1 through PREF22 contain the identifiers of the associated profiles, as defined in carpet_plan.sav.
• catalog.sav. This data file contains hypothetical monthly sales figures for three products sold by a catalog company. Data for five possible predictor variables are also included.
• catalog_seasfac.sav. This data file is the same as catalog.sav except for the addition of a set of seasonal factors calculated from the Seasonal Decomposition procedure along with the accompanying date variables.
• cellular.sav. This is a hypothetical data file that concerns a cellular phone company's efforts to reduce churn. Churn propensity scores are applied to accounts, ranging from 0 to 100. Accounts scoring 50 or above may be looking to change providers.
• ceramics.sav. This is a hypothetical data file that concerns a manufacturer's efforts to determine whether a new premium alloy has a greater heat resistance than a standard alloy. Each case represents a separate test of one of the alloys; the heat at which the bearing failed is recorded.
• cereal.sav. This is a hypothetical data file that concerns a poll of 880 people about their breakfast preferences, also noting their age, gender, marital status, and whether or not they have an active lifestyle (based on whether they exercise at least twice a week). Each case represents a separate respondent.
• clothing_defects.sav. This is a hypothetical data file that concerns the quality control process at a clothing factory. From each lot produced at the factory, the inspectors take a sample of clothes and count the number of clothes that are unacceptable.
• coffee.sav. This data file pertains to perceived images of six iced-coffee brands ⁶ . For each of 23 iced-coffee image attributes, people selected all brands that were described by the attribute. The six brands are denoted AA, BB, CC, DD, EE, and FF to preserve confidentiality.
• contacts.sav. This is a hypothetical data file that concerns the contact lists for a group of corporate computer sales representatives. Each contact is categorized by the department of the company in which they work and their company ranks. Also recorded are the amount of the last sale made, the time since the last sale, and the size of the contact's company.
• creditpromo.sav. This is a hypothetical data file that concerns a department store's efforts to evaluate the effectiveness of a recent credit card promotion. To this end, 500 cardholders were randomly selected. Half received an ad promoting a reduced interest rate on purchases made over the next three months. Half received a standard seasonal ad.
• customer_dbase.sav. This is a hypothetical data file that concerns a company's efforts to use the information in its data warehouse to make special offers to customers who are most likely to reply. A subset of the customer base was selected at random and given the special offers, and their responses were recorded.
• customer_information.sav. A hypothetical data file containing customer mailing information, such as name and address.
• customer_subset.sav. A subset of 80 cases from customer_dbase.sav.
• debate.sav. This is a hypothetical data file that concerns paired responses to a survey from attendees of a political debate before and after the debate. Each case corresponds to a separate respondent.
• debate_aggregate.sav. This is a hypothetical data file that aggregates the responses in debate.sav. Each case corresponds to a cross-classification of preference before and after the debate.
• demo.sav. This is a hypothetical data file that concerns a purchased customer database, for the purpose of mailing monthly offers. Whether or not the customer responded to the offer is recorded, along with various demographic information.
• demo_cs_1.sav. This is a hypothetical data file that concerns the first step of a company's efforts to compile a database of survey information. Each case corresponds to a different city, and the region, province, district, and city identification are recorded.
• demo_cs_2.sav. This is a hypothetical data file that concerns the second step of a company's efforts to compile a database of survey information. Each case corresponds to a different household unit from cities selected in the first step, and the region, province, district, city, subdivision, and unit identification are recorded. The sampling information from the first two stages of the design is also included.
• demo_cs.sav. This is a hypothetical data file that contains survey information collected using a complex sampling design. Each case corresponds to a different household unit, and various demographic and sampling information is recorded.
• diabetes_costs.sav. This is a hypothetical data file that contains information that is maintained by an insurance company on policy holders who have diabetes. Each case corresponds to a different policy holder.
• dietstudy.sav. This hypothetical data file contains the results of a study of the "Stillman diet" ⁷. Each case corresponds to a separate subject and records his or her pre- and post-diet weights in pounds and triglyceride levels in mg/100 ml.
• dmdata.sav. This is a hypothetical data file that contains demographic and purchasing information for a direct marketing company. dmdata2.sav contains information for a subset of contacts that received a test mailing, and dmdata3.sav contains information on the remaining contacts who did not receive the test mailing.
• dvdplayer.sav. This is a hypothetical data file that concerns the development of a new DVD player. Using a prototype, the marketing team has collected focus group data. Each case corresponds to a separate surveyed user and records some demographic information about them and their responses to questions about the prototype.
• german_credit.sav. This data file is taken from the "German credit" dataset in the Repository of Machine Learning Databases ⁸ at the University of California, Irvine.
• grocery_1month.sav. This hypothetical data file is the grocery_coupons.sav data file with the weekly purchases "rolled-up" so that each case corresponds to a separate customer. Some of the variables that changed weekly disappear as a result, and the amount spent recorded is now the sum of the amounts spent during the four weeks of the study.
• grocery_coupons.sav. This is a hypothetical data file that contains survey data collected by a grocery store chain interested in the purchasing habits of their customers. Each customer is followed for four weeks, and each case corresponds to a separate customer-week and records information about where and how the customer shops, including how much was spent on groceries during that week.
• guttman.sav. Bell ⁹ presented a table to illustrate possible social groups. Guttman ¹⁰ used a portion of this table, in which five variables describing such things as social interaction, feelings of belonging to a group, physical proximity of members, and formality of the relationship were crossed with seven theoretical social groups, including crowds (for example, people at a football game), audiences (for example, people at a theater or classroom lecture), public (for example, newspaper or television audiences), mobs (like a crowd but with much more intense interaction), primary groups (intimate), secondary groups (voluntary), and the modern community (loose confederation resulting from close physical proximity and a need for specialized services).
• health_funding.sav. This is a hypothetical data file that contains data on health care funding (amount per 100 population), disease rates (rate per 10,000 population), and visits to health care providers (rate per 10,000 population). Each case represents a different city.
• hivassay.sav. This is a hypothetical data file that concerns the efforts of a pharmaceutical lab to develop a rapid assay for detecting HIV infection. The results of the assay are eight deepening shades of red, with deeper shades indicating greater likelihood of infection. A laboratory trial was conducted on 2,000 blood samples, half of which were infected with HIV and half of which were clean.
• hourlywagedata.sav. This is a hypothetical data file that concerns the hourly wages of nurses from office and hospital positions and with varying levels of experience.
• insurance_claims.sav. This is a hypothetical data file that concerns an insurance company that wants to build a model for flagging suspicious, potentially fraudulent claims. Each case represents a separate claim.
• insure.sav. This is a hypothetical data file that concerns an insurance company that is studying the risk factors that indicate whether a client will have to make a claim on a 10-year term life insurance contract. Each case in the data file represents a pair of contracts, one of which recorded a claim and the other didn't, matched on age and gender.
• judges.sav. This is a hypothetical data file that concerns the scores given by trained judges (plus one enthusiast) to 300 gymnastics performances. Each row represents a separate performance; the judges viewed the same performances.
• kinship_dat.sav. Rosenberg and Kim ¹¹ set out to analyze 15 kinship terms (aunt, brother, cousin, daughter, father, granddaughter, grandfather, grandmother, grandson, mother, nephew, niece, sister, son, uncle). They asked four groups of college students (two female, two male) to sort these terms on the basis of similarities. Two groups (one female, one male) were asked to sort twice, with the second sorting based on a different criterion from the first sort. Thus, a total of six “sources” were obtained. Each source corresponds to a 15 x 15 proximity matrix, whose cells are equal to the number of people in a source minus the number of times the objects were partitioned together in that source.
• kinship_ini.sav. This data file contains an initial configuration for a three-dimensional solution for kinship_dat.sav.
• kinship_var.sav. This data file contains independent variables gender, gener(ation), and degree (of separation) that can be used to interpret the dimensions of a solution for kinship_dat.sav. Specifically, they can be used to restrict the space of the solution to a linear combination of these variables.
• marketvalues.sav. This data file concerns home sales in a new housing development in Algonquin, Ill., during the years from 1999–2000. These sales are a matter of public record.
• nhis2000_subset.sav. The National Health Interview Survey (NHIS) is a large, population-based survey of the U.S. civilian population. Interviews are carried out face-to-face in a nationally representative sample of households. Demographic information and observations about health behaviors and status are obtained for members of each household. This data file contains a subset of information from the 2000 survey. National Center for Health Statistics. National Health Interview Survey, 2000. Public-use data file and documentation. ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHIS/2000/. Accessed 2003.
• ozone.sav. The data include 330 observations on six meteorological variables for predicting ozone concentration from the remaining variables. Previous researchers ¹², ¹³, among others found nonlinearities among these variables, which hinder standard regression approaches.
• pain_medication.sav. This hypothetical data file contains the results of a clinical trial for anti-inflammatory medication for treating chronic arthritic pain. Of particular interest is the time it takes for the drug to take effect and how it compares to an existing medication.
• patient_los.sav. This hypothetical data file contains the treatment records of patients who were admitted to the hospital for suspected myocardial infarction (MI, or "heart attack"). Each case corresponds to a separate patient and records many variables related to their hospital stay.
• patlos_sample.sav. This hypothetical data file contains the treatment records of a sample of patients who received thrombolytics during treatment for myocardial infarction (MI, or "heart attack"). Each case corresponds to a separate patient and records many variables related to their hospital stay.
• poll_cs.sav. This is a hypothetical data file that concerns pollsters' efforts to determine the level of public support for a bill before the legislature. The cases correspond to registered voters. Each case records the county, township, and neighborhood in which the voter lives.
• poll_cs_sample.sav. This hypothetical data file contains a sample of the voters listed in poll_cs.sav. The sample was taken according to the design specified in the poll.csplan plan file, and this data file records the inclusion probabilities and sample weights. Note, however, that because the sampling plan makes use of a probability-proportional-to-size (PPS) method, there is also a file containing the joint selection probabilities (poll_jointprob.sav). The additional variables corresponding to voter demographics and their opinion on the proposed bill were collected and added the data file after the sample as taken.
• property_assess.sav. This is a hypothetical data file that concerns a county assessor's efforts to keep property value assessments up to date on limited resources. The cases correspond to properties sold in the county in the past year. Each case in the data file records the township in which the property lies, the assessor who last visited the property, the time since that assessment, the valuation made at that time, and the sale value of the property.
• property_assess_cs.sav. This is a hypothetical data file that concerns a state assessor's efforts to keep property value assessments up to date on limited resources. The cases correspond to properties in the state. Each case in the data file records the county, township, and neighborhood in which the property lies, the time since the last assessment, and the valuation made at that time.
• property_assess_cs_sample.sav. This hypothetical data file contains a sample of the properties listed in property_assess_cs.sav. The sample was taken according to the design specified in the property_assess.csplan plan file, and this data file records the inclusion probabilities and sample weights. The additional variable Current value was collected and added to the data file after the sample was taken.
• recidivism.sav. This is a hypothetical data file that concerns a government law enforcement agency's efforts to understand recidivism rates in their area of jurisdiction. Each case corresponds to a previous offender and records their demographic information, some details of their first crime, and then the time until their second arrest, if it occurred within two years of the first arrest.
• recidivism_cs_sample.sav. This is a hypothetical data file that concerns a government law enforcement agency's efforts to understand recidivism rates in their area of jurisdiction. Each case corresponds to a previous offender, released from their first arrest during the month of June, 2003, and records their demographic information, some details of their first crime, and the data of their second arrest, if it occurred by the end of June, 2006. Offenders were selected from sampled departments according to the sampling plan specified in recidivism_cs.csplan; because it makes use of a probability-proportional-to-size (PPS) method, there is also a file containing the joint selection probabilities (recidivism_cs_jointprob.sav).
• rfm_transactions.sav. A hypothetical data file containing purchase transaction data, including date of purchase, item(s) purchased, and monetary amount of each transaction.
• salesperformance.sav. This is a hypothetical data file that concerns the evaluation of two new sales training courses. Sixty employees, divided into three groups, all receive standard training. In addition, group 2 gets technical training; group 3, a hands-on tutorial. Each employee was tested at the end of the training course and their score recorded. Each case in the data file represents a separate trainee and records the group to which they were assigned and the score they received on the exam.
• satisf.sav. This is a hypothetical data file that concerns a satisfaction survey conducted by a retail company at 4 store locations. 582 customers were surveyed in all, and each case represents the responses from a single customer.
• screws.sav. This data file contains information on the characteristics of screws, bolts, nuts, and tacks ¹⁴.
• shampoo_ph.sav. This is a hypothetical data file that concerns the quality control at a factory for hair products. At regular time intervals, six separate output batches are measured and their pH recorded. The target range is 4.5–5.5.
• ships.sav. A dataset presented and analyzed elsewhere ¹⁵ that concerns damage to cargo ships caused by waves. The incident counts can be modeled as occurring at a Poisson rate given the ship type, construction period, and service period. The aggregate months of service for each cell of the table formed by the cross-classification of factors provides values for the exposure to risk.
• site.sav. This is a hypothetical data file that concerns a company's efforts to choose new sites for their expanding business. They have hired two consultants to separately evaluate the sites, who, in addition to an extended report, summarized each site as a "good," "fair," or "poor" prospect.
• smokers.sav. This data file is abstracted from the 1998 National Household Survey of Drug Abuse and is a probability sample of American households. (http://dx.doi.org/10.3886/ICPSR02934) Thus, the first step in an analysis of this data file should be to weight the data to reflect population trends.
• stocks.sav This hypothetical data file contains stocks prices and volume for one year.
• stroke_clean.sav. This hypothetical data file contains the state of a medical database after it has been cleaned using procedures in the Data Preparation option.
• stroke_invalid.sav. This hypothetical data file contains the initial state of a medical database and contains several data entry errors.
• stroke_survival. This hypothetical data file concerns survival times for patients exiting a rehabilitation program post-ischemic stroke face a number of challenges. Post-stroke, the occurrence of myocardial infarction, ischemic stroke, or hemorrhagic stroke is noted and the time of the event recorded. The sample is left-truncated because it only includes patients who survived through the end of the rehabilitation program administered post-stroke.
• stroke_valid.sav. This hypothetical data file contains the state of a medical database after the values have been checked using the Validate Data procedure. It still contains potentially anomalous cases.
• survey_sample.sav. This data file contains survey data, including demographic data and various attitude measures. It is based on a subset of variables from the 1998 NORC General Social Survey, although some data values have been modified and additional fictitious variables have been added for demonstration purposes.
• tcm_kpi.sav. This is a hypothetical data file that contains values of weekly key performance indicators for a business. It also contains weekly data for a number of controllable metrics over the same time period.
• tcm_kpi_upd.sav. This data file is identical to tcm_kpi.sav but contains data for four extra weeks.
• telco.sav. This is a hypothetical data file that concerns a telecommunications company's efforts to reduce churn in their customer base. Each case corresponds to a separate customer and records various demographic and service usage information.
• telco_extra.sav. This data file is similar to the telco.sav data file, but the "tenure" and log-transformed customer spending variables have been removed and replaced by standardized log-transformed customer spending variables.
• telco_missing.sav. This data file is a subset of the telco.sav data file, but some of the demographic data values have been replaced with missing values.
• testmarket.sav. This hypothetical data file concerns a fast food chain's plans to add a new item to its menu. There are three possible campaigns for promoting the new product, so the new item is introduced at locations in several randomly selected markets. A different promotion is used at each location, and the weekly sales of the new item are recorded for the first four weeks. Each case corresponds to a separate location-week.
• testmarket_1month.sav. This hypothetical data file is the testmarket.sav data file with the weekly sales "rolled-up" so that each case corresponds to a separate location. Some of the variables that changed weekly disappear as a result, and the sales recorded is now the sum of the sales during the four weeks of the study.
• tree_car.sav. This is a hypothetical data file containing demographic and vehicle purchase price data.
• tree_credit.sav. This is a hypothetical data file containing demographic and bank loan history data.
• tree_missing_data.sav This is a hypothetical data file containing demographic and bank loan history data with a large number of missing values.
• tree_score_car.sav. This is a hypothetical data file containing demographic and vehicle purchase price data.
• tree_textdata.sav. A simple data file with only two variables intended primarily to show the default state of variables prior to assignment of measurement level and value labels.
• tv-survey.sav. This is a hypothetical data file that concerns a survey conducted by a TV studio that is considering whether to extend the run of a successful program. 906 respondents were asked whether they would watch the program under various conditions. Each row represents a separate respondent; each column is a separate condition.
• ulcer_recurrence.sav. This file contains partial information from a study designed to compare the efficacy of two therapies for preventing the recurrence of ulcers. It provides a good example of interval-censored data and has been presented and analyzed elsewhere ¹⁶.
• ulcer_recurrence_recoded.sav. This file reorganizes the information in ulcer_recurrence.sav to allow you model the event probability for each interval of the study rather than simply the end-of-study event probability. It has been presented and analyzed elsewhere ¹⁷.
• verd1985.sav. This data file concerns a survey ¹⁸. The responses of 15 subjects to 8 variables were recorded. The variables of interest are divided into three sets. Set 1 includes age and marital, set 2 includes pet and news, and set 3 includes music and live. Pet is scaled as multiple nominal and age is scaled as ordinal; all of the other variables are scaled as single nominal.
• virus.sav. This is a hypothetical data file that concerns the efforts of an Internet service provider (ISP) to determine the effects of a virus on its networks. They have tracked the (approximate) percentage of infected e-mail traffic on its networks over time, from the moment of discovery until the threat was contained.
• wheeze_steubenville.sav. This is a subset from a longitudinal study of the health effects of air pollution on children ¹⁹. The data contain repeated binary measures of the wheezing status for children from Steubenville, Ohio, at ages 7, 8, 9 and 10 years, along with a fixed recording of whether or not the mother was a smoker during the first year of the study.
• workprog.sav. This is a hypothetical data file that concerns a government works program that tries to place disadvantaged people into better jobs. A sample of potential program participants were followed, some of whom were randomly selected for enrollment in the program, while others were not. Each case represents a separate program participant.
• worldsales.sav This hypothetical data file contains sales revenue by continent and product.