Chapter 4 The IBM SPSS Statistics Environment Flashcards

1
Q

Currency Variable

A

A variable containing values of money

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2
Q

Data Editor

A

Window where you edit data in SPSS

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3
Q

Data View

A

There are two ways to view the contents of the data editor window. The data view shows you a spreadsheet and can be used for entering raw data. See also variable view.

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4
Q

Date Variable

A

A variable made up of dates. The data can take forms such as dd-mmmm-yyyy (e.g. 21-Jun-1973), dd-mmmm-yy (e.g. 21-Jun-73), mm/dd/yy (e.g. 06/21/72), dd.mm.yyyy (e.g. 21.06.1973).

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5
Q

Long Format Data

A

Data that are arranged such that scores on an outcome variable appear in a single column and rows represent a combination of the attributed of those scores - the entity from which the scores came, when the score was recorded etc. In long format data, scores from a single entity can appear over multiple rows where each row represents a combination of the attributes of the score - for example, levels of an independent variable or time point at which the score was recorded.

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6
Q

Numeric Variables

A

Variables involving numbers

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7
Q

Smartreader

A

A free piece of software that can be downloaded from the IBM SPSS website and enables people who do not have SPSS Statistics installed to open and view SPSS output files.

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8
Q

String Variable

A

Variables involving words (e.g. letter strings). Such variables could include responses to open-ended questions such as ‘How much do you like writing glossary entries?’; the response might be ‘About as much as I like balancing my balls on hot coals’.

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9
Q

Syntax Editor

A

Window to edit predefined written commands that instruct SPSS Statistics what you would like it to do.

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10
Q

Variable View

A

There are two wards to view the contents of the data editor window. The variable view allows you to define properties of the variables for which you wish to enter data. See also data view.

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11
Q

Viewer

A

Window to view data and analyses in SPSS Statistics.

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12
Q

Wide Format Data

A

Data that are arranged such that scores from a single entity appear in a single row and levels of independent or predictor variables are arranged over different columns. As such, in designs with multiple measurements of an outcome variable within a case the outcome variable scores will be contained in multiple columns each representing a level of an independent variable, or a time point at which the score was observed. Columns can also represent attributes of the score or entity that are fixed over the duration of data collection, such as participant sex, employment status etc.

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