name: Sign contract
variables:
    legal fees: 5000
type: decision
Sign with Movie Company:
    cost: legal fees
    type: chance
    Small Box Office:
        p: 0.3
        payoff: 200000
    Medium Box Office:
        p: 0.6
        payoff: 1000000
    Large Box Office:
        p: 0.1
        payoff: 3000000
Sign with TV Network:
    payoff: 900000

## Load commands
salary <- data(salary, package = "radiant.basics", envir = environment()) %>% get()
register("salary")

## Avengers

### Variables

- name = super hero name
- alignment = good or bad character
- gender = male or female
- publisher = name of the comic publisher

Note: There is a deliberate mistake in the data. See the help file in the _Data > Combine_ tab

##  Carpet cleaner conjoint study

A respondent was presented 18 product profiles for a carpet cleaning product described on five attributes in a conjoint study.  The attributes are:

- design = Package Design (A, B, C)
- brand = Brand Name (K2R, Glory, Bissell)
- price = Price (1.19, 1.39, 1.59)
- seal = Good Housekeeping seal of approval (Yes or No)
- money_back = Money Back Guarantee (Yes or No)
- ranking = Respondent ranking of 18 attributes

Based on the attributes, 108 possible profiles could be created (i.e., 3x3x3x2x2 = 108).  The respondent was given a select set of 18 and was asked to rank the profiles from most preferred (rank of 1) to least preferred (rank of 18).  The first five columns represent the five attributes and the last column is the respondent's ranking.

## Catalog sales

### Description

Data from a company selling men's and women's apparel through mail-order catalogs. The company maintains a database on past and current customers' value and characteristics. Value is determine as the total $ sales to the customer in the last year. The data are a random sample of 200 customers from the company's database.

### Variables

A data frame with 200 observations on 4 variables

- id = Customer id
- Sales =	Total sales (in $) to a household in the past year
- Income = Household income ($1000) 
- HH.size = Size of the household (# of people) 
- Age = Age of the head of the household