**
Measurement of an Attitude**

This assignment asks you to use computers and employ either SPSS
or

Excel to explore evidence for reliability of measures. We will give you a

data set from which to work.

Here is a summary of the study from which these data were
collected.

Researchers attempted to determine if there really is anything to the

notion that fallacious reasoning is less persuasive than sound argument

(some wags claim that people are basically irrational [except for them,

of course] and that sound reasoning really does not matter in the

persuasion process). So a group of researchers took a speech and

developed examples of fallacies to represent informal fallacies in the

family of *non sequitur* (literally "not in sequence"). Two
examples of

each fallacy form were used. In contrast, a message that deleted the

fallacious arguments was included. The messages were presented on

two topics to control for topic-subject interaction.

The hypothesis to be tested was:

H_{1}: Subjects exposed to
persuasive messages including non sequitur

fallacious reasoning will exhibit
lower levels of attitude change

than subjects exposed to persuasive
message excluding non

sequitur fallacious reasoning.

Subjects were presented with the messages and then asked
to

complete a
set of four seven-point semantic differential-type scales:

wise-foolish;
good-bad; positive-negative; beneficial-harmful. These

scales are
presumed to measure attitudes toward the topic.

**Identify the level of measurement for the measure of
attitude
change **
(you may wish to write your answer to this question your own

or you may wish to use the sheet at the bottom of this web page).

To determine whether the attitude measure is reliable, it is
possible

to
examine the evidence for it. To do so, we will compute coefficient

alpha. Analysis of data is slightly different depending on whether you

use SPSS or
Excel to analyze your data. Instructions for each are

provided below.

**If you use SPSS to analyze your data, follow these
instructions:**

If you have not already done so, go to the Data
Sets location and download the file attitude.sav under the list of SPSS Files.
| |

Start your SPSS program. From the "File" menu load
the data file "ATTITUDE.SAV" from the location where the you saved it after downloading. |

Click on the "Analyze" menu, and on subsequent menus
that appear click on "Scale . . .," and "Reliability Analysis." In the "Reliability Analysis" dialog box, click on the names of the variables that compose the attitude scale: wise, good, positive, benefici. These names appear in the left window of the dialog box. Transfer each of these variables to the window marked " Items:" by clicking on the
arrow key in themiddle of the dialog box. When you have completed this process the dialog box should look as follows. |

Click on the "Statistics" button. The following
dialog box will appear. |

To keep things simple,
we will ask for essential elements of

reliability analysis only. Check the
boxes for all three

"Descriptives" as in the above box.

Click on "Continue" and "OK" in the subsequent
dialog box. Your data analysis results will appear as output and you may save these results as a file or simply interpret them directly. |

** What is the coefficient
alpha for the attitude measure **

(you may wish to write your answer to this question your own

or you may wish to use the sheet at the bottom of this

webpage).**?**

Once reliable items have been isolated, it is
a simple task to add

the reliable items together to make a composite scale. In SPSS

this step is completed by using the "Compute" from the

"Transform" menu.

**If you use Excel to analyze your data, follow these
instructions:**

If you have not already done so, go to the Data Sets location and | |

Start your Excel program. From the
"File" menu load the data file "attitude.xls" from the location where the you saved it after downloading. |

NOTE:InExcel,there is no preprogrammed reliability subroutine.

Thus, you must use your own formula. There is more than one way

to use Excel functions, but we will use a rather direct method in this

illustration. In our example, the following steps are taken.

The formula for coefficient alpha requires
that one have a variable that it is the sum of all the items on the measure. Thus, you should add the scales that are found in columns E through H on the spreadsheet. This step is accomplished by moving the cursor to the nearest empty column (column X in this case) and clicking on the first row to highlight the cell. In this cell, type "attitude," the label for the composite scale. Highlight the second row and enter "=." The formula field above the spreadsheet will be activated. Simply enter "E2+F2+G2+H2" to identify the columns that are to be added. Press "Enter" when done. |

To copy this cell down the column,
click on the cell and then select

"Copy" from the "Edit"
menu. When the cell is highlighted in this

fashion, hold down the left mouse button and
drag down the column

until all critical rows are highlighted
(through row 53 in this case).

The formula for coefficient alpha is: |

To compute coefficient alpha, we must prepare a formula. For

our data, the following formular applies:

= ((4)/3) * (1-((VAR(E2:E53))+(VAR(F2:F53))+(VAR(G2:G53))

+(VAR(H2:H53)))/(VAR(X2:X53))

Note:Though the formula takes more than one line on this page,

it is entered as one long formula. Do not forget to start the

formula with an equals sign.

To compute coefficient alpha, we need only
find a blank cell (for instance, cell Y2) and click on it to make it active. Then, the above formula may be inserted.
Once reliable items have been isolated, it
is a simple task to add the
Name
Measurement Comments for Computer Assignment
Go to "Measurement of an Attitude" found on the book
website for Chapter 8. What is the level of measurement for the dependent measure? ___________________________ Of what items is the measure composed? ________________________________________________________________
What is coefficient alpha for the scales identified as the dependent measure? ________________ |