## City distances

### Description

Distance in miles between twelve cities in the USA. The dataset is used to illustrate multi-dimensional scaling (MDS).

### Variables

A data frame with 78 observations on 3 variable.

- from = City in which travel starts
- to = City in which travel ends
- distance = Distance in miles as-the-crow-flies

## Computer positioning

### Description

The data represent consumer evaluations for a set of computers on 7 attributes. 

### Variables

A data frame with 5 rows of data on 8 variables. All numbers are averages across respondents.

- brand = The computer brand name
- high_end = Is the brand perceived to be highend (1-9), where 1 is not at all highend and 9 is very highend
- stylish = Is the brand perceived to be stylish (1-9), where 1 is not at all stylish and 9 is very stylish
- modern = Is the brand perceived as modern (1-9), where 1 is not at all modern and 9 is very modern
- value = Is the brand perceived to offer good value (1-9), where 1 is not at all good value and 9 is very good value
- dated = Is the brand perceived to have a dated look (1-9), where 1 is not at all dated and 9 is very dated
- innovative = Is the brand perceived to an innovation leader (1-9), where 1 is not at all and 9 is very much
- business = Is the brand perceived to have a business orientation (1-9), where 1 is not at all and 9 is very much

## Car brand consideration 

### Description

A car manufacturers conducted a study by randomly sampling and interviewing 1,000 consumers in a new target market to determine if consumers would consider purchasing this brand of car.

Management has already determined that the company will enter this segment. However, if brand preference is lower than 10% additional resources will be committed to advertising and sponsorship in an effort to enhance brand awareness amongst the target consumers. In the sample, 93 consumers exhibited what the company the company considered strong liking.

### Variables 

The data set has 1000 rows and two variables, `id` and `consider`. 

* id = Survey respondent id
* consider = Would the consumer consider purchasing this brand of car (yes / no)?