# Question Types

(Redirected from Pick Any - Grid)
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Question Types and Statistics
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Part 3 of Creating and Modifying Variables (Video)

The way that Q presents data is determined by the underlying Question Type of the data. These are set automatically when importing data and can be modified in the Variables and Questions tab.

## Text

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Coding Text Variables
Back-Coding
Coding Spontaneous Awareness
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Each observation in the data file contains text. For example, data obtained from a question like:

Please enter the name of the last soft drink you bought.

_____________

Text questions are created from Text Variables, which are either included in the original data file, Pasted Variables or are created as JavaScript Text Variables.

Text questions are transformed into other types of questions by changing Variable Type or Coding.

## Text - Multi

Multiple related fields of text for each observation in the data file. For example, from a question like:

1.____________

2.____________

3.____________

Text - Multi questions are sets of two or more Text Variables.

## Pick One

A series of mutually exclusive and exhaustive categories (i.e., nominal or Ordinal scales). A Pick One question can be created from all non-Text Variables. For example:

Are you...

o Male

o Female

## Pick One - Multi

A set of categorical variables sharing the same scale points.

Low Medium High
McDonald's o o o
Burger King o o o
Wendy's o o o

## Number

A numeric variable (i.e., interval or ratio scale). For example:

How many glasses of wine did you drink last night? ____

## Number - Multi

A series of numeric variables measured on the same scale. For example:

Next to the brands below, please indicate how many times you have purchased them in the past week.

Coke ___

Pepsi ___

Fanta ___

## Number - Grid

Similar to a Number - Multi question except that the variables can be thought of as being ordered in two dimensions. For example:

In the past month, how many economy flights did you take on...

Qantas ___ United ___ SAS ___

In the past month, how many business class flights did you take on...

Qantas ___ United ___ SAS ___

Q infers the structure of the grid by inspecting the variables' labels at the time of importing the data; where Q cannot discern the structure of the data this can be set using Grid Layout, which is shown when using Set Question to create a grid question.

## Pick Any

What is usually referred to in market research as a multiple response or multi-response question. Essentially, it is a type of Pick One - Multi question where there are only two categories in each variable. The most common examples relate to non-mutually exclusive categories.

Which of the following have you bought in the past week? Tick all that apply.

[] Coke

[] Pepsi

[] Fanta

[] None of these

## Pick Any - Compact

The same as a Pick Any question stored in a max-multi format; first variable contains first response, second variable contains second response, etc. This format should only be used to represent multiple response data when there are truly huge code frames (e.g., thousands of options). It is generally inferior to a Pick Any format as it is unwieldy for data manipulation (e.g., for use in formulas) and it cannot accommodate the notion of missing data.

Prior to version 4.7.4, all cases were treated as having data. From 4.7.4, cases with no data were treated as missing.

## Pick Any - Grid

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Poorly Set Up Grids
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Similar to a A Pick Any question where the variables can be thought of as being ordered in two dimensions.

Which of these brands are fun?

 [] Coke [] Pepsi [] Fanta

Which of these brands are sexy?

 [] Coke [] Pepsi [] Fanta

Which of these brands are masculine?

 [] Coke [] Pepsi [] Fanta

Q infers the structure of the grid by inspecting the variables' labels at the time of importing the data; where Q cannot discern the structure of the data this can be set using Grid Layout, which is shown when using Set Question to create a grid question. For a worked example of how to setup labels and variables to be recognized as a grid see our blog here

## Date

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Time Series Plots
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A question containing a single date variable. Most commonly they are automatically created in data files (e.g., time stamps for when interviews are completed), but they can also be obtained as questions:

What is your date of birth?

____ / ____ / ____

Date questions can be used like any other question except for dragging and dropping to merge categories, i.e., they can be crosstabbed, used to create filters, etc.

Date questions are useful for easily changing between different time periods (e.g., weekly to quarterly data) and for creating moving averages and other smoothers (see time series charts, Time Series Analysis and moving average questions.

A Date Variable can be turned into a Date question in the Variables and Questions tab by selecting the variable and selecting Set Question or by changing the Question Type.

Dates can converted to different time scales (e.g., months, weeks, quarters) by right-clicking on a data (either in a table or the dates shown in a chart) and selecting Values.

## Ranking

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Rankings
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Multiple numeric variables that represent a ranking, where the highest number is most preferred and ties are permitted. For example:

Rank the following brands according to how much you like them... Please a 3 next to the brand you like most, a 2 in your next preferred brand and a 1 next to your least preferred brand.

Coke ____

Pepsi ____

Fanta ____

Note that if your question uses lowest numbers as indicating alternatives being more preferred you will need to reverse the Value assigned to each rank in the Value Attributes.

When creating Segments, using Smart Tables and creating Trees it is generally recommended to use the Ranking type as it is, in a statistical sense, the best representation of the data. However, this question type is difficult to understand and even more difficult to explain to end users and should often be avoided when preparing final results so as to avoid confusion.

## Experiment

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This question type is used to represent the various different types of experiments, from randomized experiments (Fully randomized experiments through to Conjoint Analysis and Choice Modeling). See Experiments for more information.

Which of these would you buy?

 Coke Pepsi Fanta $2.00$2.10 \$1.80 o o o