UW Psychology Question
Description
Introduction to research methods, 2nd year psychology course, complete 1 assignment, using SPSS software. Require full marks in the course.
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7
I Will Remember You
One topic of central interest to both experimental psychologists and the public is the
accuracy of the human memory. Barlett (1932) is usually credited with conducting the
first investigations of false memories, remembrances of events that never occurred. He
studied distortions of memory using a complex prose passage. Participants read a folktale
The War of the Ghosts and tried to recall it repeatedly. Results showed that
participants memories became more and more distorted over repeated attempts to recall.
These results suggest that everyday memory is not always as reliable and faithful
reproduction of the past, a static snapshot of events as they truly were. Instead, memory is
sometimes fallible, imperfect and reconstructive, and shaped by present circumstances.
While these conclusions about the fallibility of everyday memory seem justified, it is
conceivable that memory distortion occurs only under restricted conditions. It is perhaps
not surprising that participants found it difficult to retell a story, rich and complex in
meaning, in exactly the same way. Should not some variability be expected in storytelling? Indeed, it is quite possible that Barletts participants were themselves aware that
the story was changing with repeated tellings. His findings would surely be strengthened
if it were found that participants were totally unaware of the intrusions of irrelevant
material into their story. In addition, it would be of some interest to know whether
memory distortion occurs in other paradigms, for example, serial-list learning.
In serial-list learning, the experimenter reads aloud a list of words and the participants
memorize and then later try to recall each of the presented words. The words are usually
presented one-by-one in short lists comprised of 15 or so items. The recall test involved
the participants listing, in written form, the items they can remember from the studied
list. Often, a recognition test is included. In the recognition test, the experimenter
provides a list of words, which contains items from the studied lists and lures, words
never presented. Participants indicate their level of confidence about whether each item
had occurred. The task is often made more difficult by presenting multiple lists.
Remembering words not presented, or recognizing them, would constitute a false
memory.
Common sense would suggest that remembering or recognizing words not presented
should occur with low frequency. In addition, if participants did misremember words,
they should not express high confidence that a particular misremembered word was
actually in the list. In a recognition test, for example, they may agree that a non-studied
item was probably in the list, when it was not, but they should never state with
complete assurance that they had actually heard it. And, indeed, they should be incapable
of actually recollecting the moment at which the word was read by the experimenter,
since it was never actually presented.
Procedure
Two experimenters will read prepared lists of words aloud. After each list is read,
participants will immediately write down as many words as they can remember on for 1
minute each. When all of the lists are completed, participants will be given a recognition
test, which contains studied and non-studied items. For each item, the students will rate
whether it was a) surely new, b) probably new, c) probably old, or d) surely old. If the
item was rated as surely old, participants should indicate which of the two experimenters
they remembered uttered the word.
References
Barlett, F.C. (1932). Remembering: A study in experimental and social psychology.
Cambridge University Press.
Questions
1. Answer the following questions.
a. Identify the independent variable and the levels of the independent
variable. (0.5 point)
b. Identify the dependent variable. (0.5 point)
c. Outline your theory of memory. (1 point)
d. What is the experimental hypothesis? (1 point)
2. What percentages of the studied and non-studied items were recognized as a)
surely old, b) probably old, c) probably new, and d) surely new? Break the nonstudied items into unrelated lures, weakly related lures, and critical lures. To
answer this question, present the data in a 4 x 4 APA style table with the levels of
independent variable listed in separate rows and the levels of the dependent
variable listed in separate columns. In the table, there should be four levels of
item status (studied, non-studied/unrelated lure, non-studied/weakly related lure,
and non-studied/critical lure) and four possible responses (surely old, probably
old, probably new, and surely new). (2 points)
3. Answer the following questions.
a. With regard to the critical lures, what percentage of the critical lures were
classified as surely old? (0.5 point)
b. What percentage of the participants said the critical lures were surely
old? (0.5 point)
c. What percentage of the participants that classified a critical lure as surely
old indicated they remembered which experimenter had uttered the
critical lure (a word never actually presented)? (0.5 point)
4. Do the results support the experimental hypothesis? Be sure to provide an
explanation by referring to the results. (1.5 points)
5. People often say they vividly remember the details surrounding a particular event,
which attests to the fact that memory cannot be false. What do our data have to
say about this issue? (2 points)
The following four questions are designed to get you to explore the interaction between
item relatedness (i.e., critical/related versus unrelated) and item classification (i.e., old
versus new).
6. Your instructor had provided you with a SPSS data file that has combined
categories; that is, lures classified as probably new or surely new should be
considered new and lures classified as probably old or surely old should be
considered old. Use SPSS (instructions below) to obtain the mean number of
items in each of the four categories (critical lure/new, critical lure/old, unrelated
lure/new, unrelated lure/old).
7. Use the means obtained in the previous question to produce an APA style line
graph with the mean number of items recognized along the y-axis, the type of lure
(critical or unrelated) along the x-axis, and define the lines by the classification
category (new/old). You can do this using SPSS (instructions below). (2 points)
8. Use the line graph to describe whether there is an interaction (between type of
word and classification category). (1 point)
9. Use SPSS to determine whether the interaction between type of word and
classification category is statistically significant. Describe the findings using APA
style. Use the p-value to assess statistical significance. Recall, if p-value = a,
reject H0 (result is statistically significant.) (1.5 points)
Report Preparation
Prepare a neat and tidy lab report. It is recommended that you type your lab report. Your
report should include the following:
APA style title page
SPSS output
Answers to the nine questions.
Lab Total: 14.5 points
SPSS Instructions for Analyzing Main Effects and Interactions
DATA ENTRY Your lab instructor has converted the Qualtrics data from Excel
into an SPSS file that you may download from Nexus. Instructions 1 to 9
below are associated with copying, pasting, and creating data from the Excel
spreadsheet without the Qualtrics compilation and Macros conversion of the
Excel data. You may download and open the SPSS file provided, skip
instructions 1 to 9 and begin with number 10, Create an output file.
1. On the Variable View tab of the Data Editor create three variables: lure,
classcat, and count.
Name
lure
Type
Numeric
Decimals
0
Label
Type of Lure
classcat
Numeric
0
Classification
Category
surely
probably
Numeric
Numeric
0
0
Values
1 = unrelated
2 = critical
1 = old
2 = new
2. Copy and paste the data from Excel into SPSS.
a. Copy the values from the Unstudied-Unrelated Lure SO (surely old)
column in Excel and paste them into the surely variable in SPSS. For the
lure variable enter a value of 1 and for the classcat variable enter a value
of 1.
b. Copy the values from the Unstudied-Unrelated Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column from part a).
c. Copy the values from the Unstudied-Unrelated Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part b). For the lure variable enter a value of 1 and for the
classcat variable enter a value of 2.
d. Copy the values from the Unstudied-Unrelated Lure SN (surely new)
column in Excel and paste them into the surely variable in SPSS (next to
the values in the probably column that your pasted in part c).
e. Copy the values from the Unstudied-Critical Lure SO (surely old) column
in Excel and paste them into the surely variable in SPSS (below the values
from part b). For the lure variable enter a value of 2 and for the classcat
variable enter a value of 1.
f. Copy the values from the Unstudied-Critical Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column that you pasted from part e).
g. Copy the values from the Unstudied-Critical Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part f). For the lure variable enter a value of 2 and for the
classcat variable enter a value of 2.
h. Copy the values from the Unstudied-Critical Lure SN (surely new) column
in Excel and paste them into the surely variable in SPSS (next to the
values in the probably column that you pasted from part g).
lure = 1 (Unstudied-Unrelated)
classcat = 1 (Old)
lure = 1 (Unstudied-Unrelated)
classcat = 2 (New)
lure = 2 (Unstudied-Critical)
classcat = 1 (Old)
3. Create a new variable, count, representing the total number of words in the surely
and probably columns. Note were creating old and new categories by
combining surely old and probably old into old and surely new and probably
new into new. To create this variable select Compute from the Transform
menu.
4. The Compute Variable dialog box will appear.
5. In the Target Variable: box type count.
6. In the Numeric Expression box build the equation. Select surely and click the
arrow between the two boxes. Click the + button. Select probably and click the
arrow between the two boxes. In the Numeric Expression box you should have
surely + probably.
7. Click OK.
8. On the Variable View tab change the number of decimal places for the count
variable to 0 and enter Number of Words as the label for count.
9. Save the file as Lab7 to your home directory. To save the file, on the File menu,
select Save As, and then follow the path to your home directory by clicking on the
appropriate sequence of folders in the Save in box. Now, in the box next to File
name: type Lab7 and then click Save. The file will be saved with the .sav
extension.
CREATE AN OUTPUT FILE
10. The Output window is where SPSS puts the results of the analyses.
a. To open a new output window select New and then Output from the File
menu. Please note that a new output window may have automatically
opened when you saved the data file so you may be able to skip this step.
b. You need to be able to distinguish your output when it is printed from
your classmates. We do this by putting our last name and student number
at the top of the output file. In SPSS, select New Title on the Insert menu.
Enter your last name and student number (e.g., Halldorson, 5430718) into
the box. Exit the box by clicking out of it twice.
ANALYSIS
11. To obtain the means for each combination of the levels of the two variables and to
determine the significance of the main effects and interaction, select General
Linear Model and then Univariate from the Analyze menu.
12. The Univariate dialogue box will appear (as shown below). Place the count
variable (Number of Words) into the Dependent Variable: box by selecting the
variable and clicking on the arrow between the two boxes.
13. Place both lure (Type of Lure) and classcat (Classification Category) into the
Fixed Factor(s): box by selecting the two variables and clicking the arrow
between the two boxes.
14. To obtain the means for each combination of factor levels, click the Options
button. The Univariate: Options box will appear.
15. Under Display, click the box next to Descriptive statistics. A check mark should
appear.
16. Click Continue.
(Your options display may look different.)
17. Click the Model button. The Univariate: Model dialog box should appear.
Check that the radio button next to Full Factorial is selected.
18. Click Continue.
19. Click OK.
The Output produced should include the Tests of Between-Subjects Effects table (see
below).
Tests of Between-Subjects Effects
Dependent Variable: Number of Words
Source
Corrected Model
Intercept
lure
clas s cat
lure * clas scat
Error
Total
Corrected Total
Type III Sum
of Squares
17.800a
320.000
.000
5.000
12.800
162.200
500.000
180.000
p-values
df
3
1
1
1
1
76
80
79
Mean Square
5.933
320.000
.000
5.000
12.800
2.134
F
2.780
149.938
.000
2.343
5.998
a. R Squared = .099 (Adjusted R Squared = .063)
Main effect of Type of Lure
Main Effect of Classification Category
Interaction between Type of Lure and Classification Category
Sig.
.047
.000
1.000
.130
.017
Line Graph
20. On the Graphs menu select Legacy Dialogs, then Line
21. The Line Charts dialog box should appear. Click on Multiple and then click
Define.
22. The define Multiple Line: Summaries for Groups of Cases dialog box should
appear.
23. Place lure (Type of Lure) into the Category Axis: box by selecting the variable
and clicking the arrow between the two boxes.
24. Place classcat (Classification Category) into the Define Lines by: box by
selecting the variable and clicking the arrow between the two boxes.
25. Click the radio button next to Other Statistic (e.g., mean).
26. Select the count variable (Number of Words) and place it into the Variable: box
by clicking the arrow between the two buttons.
27. Click OK.
28. Be sure to add a figure title and edit the graph so it follows APA 7 graphing
conventions. It should look similar to the following:
SAVE YOUR OUTPUT FILE
29. The output file needs to be saved as a separate file (different from the data file).
To save the output file, click on the File menu and select Save As. Just like the
data file, follow the path to your home directory in the Save in box. To save the
file, in the box next to File name: type Lab7 and then click Save. You can use
the same file name as the data file because the two files are saved with different
extensions. The output file will be saved with the .spv extension.
EXPORTING YOUR OUTPUT TO A WORD DOCUMENT
30. If you want to export your output to WORD and submitted as a Word file, follow
these instructions: With your output open, click on the File menu and select
Export . The Export Output dialogue box should appear. You will need to
change three things. 1) Under Objects to Export, select the radio button next to
All Visible (change from the default All). 2) Under Document: Type: select the
down arrow and change the format to Word/RTF file (*.doc), if necessary. 3)
Click the Browse button. The Save As dialogue box will appear. Follow the
path to your home directory in the Look in box and name the file (the default is
OUTPUT.doc). Click Save and OK. Be sure to check the Word file to make sure
the output was exported properly.
Homework
Work on your presentation and paper for Lab #8: Stairway to Heaven
7
I Will Remember You
One topic of central interest to both experimental psychologists and the public is the
accuracy of the human memory. Barlett (1932) is usually credited with conducting the
first investigations of false memories, remembrances of events that never occurred. He
studied distortions of memory using a complex prose passage. Participants read a folktale
The War of the Ghosts and tried to recall it repeatedly. Results showed that
participants memories became more and more distorted over repeated attempts to recall.
These results suggest that everyday memory is not always as reliable and faithful
reproduction of the past, a static snapshot of events as they truly were. Instead, memory is
sometimes fallible, imperfect and reconstructive, and shaped by present circumstances.
While these conclusions about the fallibility of everyday memory seem justified, it is
conceivable that memory distortion occurs only under restricted conditions. It is perhaps
not surprising that participants found it difficult to retell a story, rich and complex in
meaning, in exactly the same way. Should not some variability be expected in storytelling? Indeed, it is quite possible that Barletts participants were themselves aware that
the story was changing with repeated tellings. His findings would surely be strengthened
if it were found that participants were totally unaware of the intrusions of irrelevant
material into their story. In addition, it would be of some interest to know whether
memory distortion occurs in other paradigms, for example, serial-list learning.
In serial-list learning, the experimenter reads aloud a list of words and the participants
memorize and then later try to recall each of the presented words. The words are usually
presented one-by-one in short lists comprised of 15 or so items. The recall test involved
the participants listing, in written form, the items they can remember from the studied
list. Often, a recognition test is included. In the recognition test, the experimenter
provides a list of words, which contains items from the studied lists and lures, words
never presented. Participants indicate their level of confidence about whether each item
had occurred. The task is often made more difficult by presenting multiple lists.
Remembering words not presented, or recognizing them, would constitute a false
memory.
Common sense would suggest that remembering or recognizing words not presented
should occur with low frequency. In addition, if participants did misremember words,
they should not express high confidence that a particular misremembered word was
actually in the list. In a recognition test, for example, they may agree that a non-studied
item was probably in the list, when it was not, but they should never state with
complete assurance that they had actually heard it. And, indeed, they should be incapable
of actually recollecting the moment at which the word was read by the experimenter,
since it was never actually presented.
Procedure
Two experimenters will read prepared lists of words aloud. After each list is read,
participants will immediately write down as many words as they can remember on for 1
minute each. When all of the lists are completed, participants will be given a recognition
test, which contains studied and non-studied items. For each item, the students will rate
whether it was a) surely new, b) probably new, c) probably old, or d) surely old. If the
item was rated as surely old, participants should indicate which of the two experimenters
they remembered uttered the word.
References
Barlett, F.C. (1932). Remembering: A study in experimental and social psychology.
Cambridge University Press.
Questions
1. Answer the following questions.
a. Identify the independent variable and the levels of the independent
variable. (0.5 point)
b. Identify the dependent variable. (0.5 point)
c. Outline your theory of memory. (1 point)
d. What is the experimental hypothesis? (1 point)
2. What percentages of the studied and non-studied items were recognized as a)
surely old, b) probably old, c) probably new, and d) surely new? Break the nonstudied items into unrelated lures, weakly related lures, and critical lures. To
answer this question, present the data in a 4 x 4 APA style table with the levels of
independent variable listed in separate rows and the levels of the dependent
variable listed in separate columns. In the table, there should be four levels of
item status (studied, non-studied/unrelated lure, non-studied/weakly related lure,
and non-studied/critical lure) and four possible responses (surely old, probably
old, probably new, and surely new). (2 points)
3. Answer the following questions.
a. With regard to the critical lures, what percentage of the critical lures were
classified as surely old? (0.5 point)
b. What percentage of the participants said the critical lures were surely
old? (0.5 point)
c. What percentage of the participants that classified a critical lure as surely
old indicated they remembered which experimenter had uttered the
critical lure (a word never actually presented)? (0.5 point)
4. Do the results support the experimental hypothesis? Be sure to provide an
explanation by referring to the results. (1.5 points)
5. People often say they vividly remember the details surrounding a particular event,
which attests to the fact that memory cannot be false. What do our data have to
say about this issue? (2 points)
The following four questions are designed to get you to explore the interaction between
item relatedness (i.e., critical/related versus unrelated) and item classification (i.e., old
versus new).
6. Your instructor had provided you with a SPSS data file that has combined
categories; that is, lures classified as probably new or surely new should be
considered new and lures classified as probably old or surely old should be
considered old. Use SPSS (instructions below) to obtain the mean number of
items in each of the four categories (critical lure/new, critical lure/old, unrelated
lure/new, unrelated lure/old).
7. Use the means obtained in the previous question to produce an APA style line
graph with the mean number of items recognized along the y-axis, the type of lure
(critical or unrelated) along the x-axis, and define the lines by the classification
category (new/old). You can do this using SPSS (instructions below). (2 points)
8. Use the line graph to describe whether there is an interaction (between type of
word and classification category). (1 point)
9. Use SPSS to determine whether the interaction between type of word and
classification category is statistically significant. Describe the findings using APA
style. Use the p-value to assess statistical significance. Recall, if p-value = a,
reject H0 (result is statistically significant.) (1.5 points)
Report Preparation
Prepare a neat and tidy lab report. It is recommended that you type your lab report. Your
report should include the following:
APA style title page
SPSS output
Answers to the nine questions.
Lab Total: 14.5 points
SPSS Instructions for Analyzing Main Effects and Interactions
DATA ENTRY Your lab instructor has converted the Qualtrics data from Excel
into an SPSS file that you may download from Nexus. Instructions 1 to 9
below are associated with copying, pasting, and creating data from the Excel
spreadsheet without the Qualtrics compilation and Macros conversion of the
Excel data. You may download and open the SPSS file provided, skip
instructions 1 to 9 and begin with number 10, Create an output file.
1. On the Variable View tab of the Data Editor create three variables: lure,
classcat, and count.
Name
lure
Type
Numeric
Decimals
0
Label
Type of Lure
classcat
Numeric
0
Classification
Category
surely
probably
Numeric
Numeric
0
0
Values
1 = unrelated
2 = critical
1 = old
2 = new
2. Copy and paste the data from Excel into SPSS.
a. Copy the values from the Unstudied-Unrelated Lure SO (surely old)
column in Excel and paste them into the surely variable in SPSS. For the
lure variable enter a value of 1 and for the classcat variable enter a value
of 1.
b. Copy the values from the Unstudied-Unrelated Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column from part a).
c. Copy the values from the Unstudied-Unrelated Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part b). For the lure variable enter a value of 1 and for the
classcat variable enter a value of 2.
d. Copy the values from the Unstudied-Unrelated Lure SN (surely new)
column
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I Will Remember You
One topic of central interest to both experimental psychologists and the public is the
accuracy of the human memory. Barlett (1932) is usually credited with conducting the
first investigations of false memories, remembrances of events that never occurred. He
studied distortions of memory using a complex prose passage. Participants read a folktale
The War of the Ghosts and tried to recall it repeatedly. Results showed that
participants memories became more and more distorted over repeated attempts to recall.
These results suggest that everyday memory is not always as reliable and faithful
reproduction of the past, a static snapshot of events as they truly were. Instead, memory is
sometimes fallible, imperfect and reconstructive, and shaped by present circumstances.
While these conclusions about the fallibility of everyday memory seem justified, it is
conceivable that memory distortion occurs only under restricted conditions. It is perhaps
not surprising that participants found it difficult to retell a story, rich and complex in
meaning, in exactly the same way. Should not some variability be expected in storytelling? Indeed, it is quite possible that Barletts participants were themselves aware that
the story was changing with repeated tellings. His findings would surely be strengthened
if it were found that participants were totally unaware of the intrusions of irrelevant
material into their story. In addition, it would be of some interest to know whether
memory distortion occurs in other paradigms, for example, serial-list learning.
In serial-list learning, the experimenter reads aloud a list of words and the participants
memorize and then later try to recall each of the presented words. The words are usually
presented one-by-one in short lists comprised of 15 or so items. The recall test involved
the participants listing, in written form, the items they can remember from the studied
list. Often, a recognition test is included. In the recognition test, the experimenter
provides a list of words, which contains items from the studied lists and lures, words
never presented. Participants indicate their level of confidence about whether each item
had occurred. The task is often made more difficult by presenting multiple lists.
Remembering words not presented, or recognizing them, would constitute a false
memory.
Common sense would suggest that remembering or recognizing words not presented
should occur with low frequency. In addition, if participants did misremember words,
they should not express high confidence that a particular misremembered word was
actually in the list. In a recognition test, for example, they may agree that a non-studied
item was probably in the list, when it was not, but they should never state with
complete assurance that they had actually heard it. And, indeed, they should be incapable
of actually recollecting the moment at which the word was read by the experimenter,
since it was never actually presented.
Procedure
Two experimenters will read prepared lists of words aloud. After each list is read,
participants will immediately write down as many words as they can remember on for 1
minute each. When all of the lists are completed, participants will be given a recognition
test, which contains studied and non-studied items. For each item, the students will rate
whether it was a) surely new, b) probably new, c) probably old, or d) surely old. If the
item was rated as surely old, participants should indicate which of the two experimenters
they remembered uttered the word.
References
Barlett, F.C. (1932). Remembering: A study in experimental and social psychology.
Cambridge University Press.
Questions
1. Answer the following questions.
a. Identify the independent variable and the levels of the independent
variable. (0.5 point)
b. Identify the dependent variable. (0.5 point)
c. Outline your theory of memory. (1 point)
d. What is the experimental hypothesis? (1 point)
2. What percentages of the studied and non-studied items were recognized as a)
surely old, b) probably old, c) probably new, and d) surely new? Break the nonstudied items into unrelated lures, weakly related lures, and critical lures. To
answer this question, present the data in a 4 x 4 APA style table with the levels of
independent variable listed in separate rows and the levels of the dependent
variable listed in separate columns. In the table, there should be four levels of
item status (studied, non-studied/unrelated lure, non-studied/weakly related lure,
and non-studied/critical lure) and four possible responses (surely old, probably
old, probably new, and surely new). (2 points)
3. Answer the following questions.
a. With regard to the critical lures, what percentage of the critical lures were
classified as surely old? (0.5 point)
b. What percentage of the participants said the critical lures were surely
old? (0.5 point)
c. What percentage of the participants that classified a critical lure as surely
old indicated they remembered which experimenter had uttered the
critical lure (a word never actually presented)? (0.5 point)
4. Do the results support the experimental hypothesis? Be sure to provide an
explanation by referring to the results. (1.5 points)
5. People often say they vividly remember the details surrounding a particular event,
which attests to the fact that memory cannot be false. What do our data have to
say about this issue? (2 points)
The following four questions are designed to get you to explore the interaction between
item relatedness (i.e., critical/related versus unrelated) and item classification (i.e., old
versus new).
6. Your instructor had provided you with a SPSS data file that has combined
categories; that is, lures classified as probably new or surely new should be
considered new and lures classified as probably old or surely old should be
considered old. Use SPSS (instructions below) to obtain the mean number of
items in each of the four categories (critical lure/new, critical lure/old, unrelated
lure/new, unrelated lure/old).
7. Use the means obtained in the previous question to produce an APA style line
graph with the mean number of items recognized along the y-axis, the type of lure
(critical or unrelated) along the x-axis, and define the lines by the classification
category (new/old). You can do this using SPSS (instructions below). (2 points)
8. Use the line graph to describe whether there is an interaction (between type of
word and classification category). (1 point)
9. Use SPSS to determine whether the interaction between type of word and
classification category is statistically significant. Describe the findings using APA
style. Use the p-value to assess statistical significance. Recall, if p-value = a,
reject H0 (result is statistically significant.) (1.5 points)
Report Preparation
Prepare a neat and tidy lab report. It is recommended that you type your lab report. Your
report should include the following:
APA style title page
SPSS output
Answers to the nine questions.
Lab Total: 14.5 points
SPSS Instructions for Analyzing Main Effects and Interactions
DATA ENTRY Your lab instructor has converted the Qualtrics data from Excel
into an SPSS file that you may download from Nexus. Instructions 1 to 9
below are associated with copying, pasting, and creating data from the Excel
spreadsheet without the Qualtrics compilation and Macros conversion of the
Excel data. You may download and open the SPSS file provided, skip
instructions 1 to 9 and begin with number 10, Create an output file.
1. On the Variable View tab of the Data Editor create three variables: lure,
classcat, and count.
Name
lure
Type
Numeric
Decimals
0
Label
Type of Lure
classcat
Numeric
0
Classification
Category
surely
probably
Numeric
Numeric
0
0
Values
1 = unrelated
2 = critical
1 = old
2 = new
2. Copy and paste the data from Excel into SPSS.
a. Copy the values from the Unstudied-Unrelated Lure SO (surely old)
column in Excel and paste them into the surely variable in SPSS. For the
lure variable enter a value of 1 and for the classcat variable enter a value
of 1.
b. Copy the values from the Unstudied-Unrelated Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column from part a).
c. Copy the values from the Unstudied-Unrelated Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part b). For the lure variable enter a value of 1 and for the
classcat variable enter a value of 2.
d. Copy the values from the Unstudied-Unrelated Lure SN (surely new)
column in Excel and paste them into the surely variable in SPSS (next to
the values in the probably column that your pasted in part c).
e. Copy the values from the Unstudied-Critical Lure SO (surely old) column
in Excel and paste them into the surely variable in SPSS (below the values
from part b). For the lure variable enter a value of 2 and for the classcat
variable enter a value of 1.
f. Copy the values from the Unstudied-Critical Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column that you pasted from part e).
g. Copy the values from the Unstudied-Critical Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part f). For the lure variable enter a value of 2 and for the
classcat variable enter a value of 2.
h. Copy the values from the Unstudied-Critical Lure SN (surely new) column
in Excel and paste them into the surely variable in SPSS (next to the
values in the probably column that you pasted from part g).
lure = 1 (Unstudied-Unrelated)
classcat = 1 (Old)
lure = 1 (Unstudied-Unrelated)
classcat = 2 (New)
lure = 2 (Unstudied-Critical)
classcat = 1 (Old)
3. Create a new variable, count, representing the total number of words in the surely
and probably columns. Note were creating old and new categories by
combining surely old and probably old into old and surely new and probably
new into new. To create this variable select Compute from the Transform
menu.
4. The Compute Variable dialog box will appear.
5. In the Target Variable: box type count.
6. In the Numeric Expression box build the equation. Select surely and click the
arrow between the two boxes. Click the + button. Select probably and click the
arrow between the two boxes. In the Numeric Expression box you should have
surely + probably.
7. Click OK.
8. On the Variable View tab change the number of decimal places for the count
variable to 0 and enter Number of Words as the label for count.
9. Save the file as Lab7 to your home directory. To save the file, on the File menu,
select Save As, and then follow the path to your home directory by clicking on the
appropriate sequence of folders in the Save in box. Now, in the box next to File
name: type Lab7 and then click Save. The file will be saved with the .sav
extension.
CREATE AN OUTPUT FILE
10. The Output window is where SPSS puts the results of the analyses.
a. To open a new output window select New and then Output from the File
menu. Please note that a new output window may have automatically
opened when you saved the data file so you may be able to skip this step.
b. You need to be able to distinguish your output when it is printed from
your classmates. We do this by putting our last name and student number
at the top of the output file. In SPSS, select New Title on the Insert menu.
Enter your last name and student number (e.g., Halldorson, 5430718) into
the box. Exit the box by clicking out of it twice.
ANALYSIS
11. To obtain the means for each combination of the levels of the two variables and to
determine the significance of the main effects and interaction, select General
Linear Model and then Univariate from the Analyze menu.
12. The Univariate dialogue box will appear (as shown below). Place the count
variable (Number of Words) into the Dependent Variable: box by selecting the
variable and clicking on the arrow between the two boxes.
13. Place both lure (Type of Lure) and classcat (Classification Category) into the
Fixed Factor(s): box by selecting the two variables and clicking the arrow
between the two boxes.
14. To obtain the means for each combination of factor levels, click the Options
button. The Univariate: Options box will appear.
15. Under Display, click the box next to Descriptive statistics. A check mark should
appear.
16. Click Continue.
(Your options display may look different.)
17. Click the Model button. The Univariate: Model dialog box should appear.
Check that the radio button next to Full Factorial is selected.
18. Click Continue.
19. Click OK.
The Output produced should include the Tests of Between-Subjects Effects table (see
below).
Tests of Between-Subjects Effects
Dependent Variable: Number of Words
Source
Corrected Model
Intercept
lure
clas s cat
lure * clas scat
Error
Total
Corrected Total
Type III Sum
of Squares
17.800a
320.000
.000
5.000
12.800
162.200
500.000
180.000
p-values
df
3
1
1
1
1
76
80
79
Mean Square
5.933
320.000
.000
5.000
12.800
2.134
F
2.780
149.938
.000
2.343
5.998
a. R Squared = .099 (Adjusted R Squared = .063)
Main effect of Type of Lure
Main Effect of Classification Category
Interaction between Type of Lure and Classification Category
Sig.
.047
.000
1.000
.130
.017
Line Graph
20. On the Graphs menu select Legacy Dialogs, then Line
21. The Line Charts dialog box should appear. Click on Multiple and then click
Define.
22. The define Multiple Line: Summaries for Groups of Cases dialog box should
appear.
23. Place lure (Type of Lure) into the Category Axis: box by selecting the variable
and clicking the arrow between the two boxes.
24. Place classcat (Classification Category) into the Define Lines by: box by
selecting the variable and clicking the arrow between the two boxes.
25. Click the radio button next to Other Statistic (e.g., mean).
26. Select the count variable (Number of Words) and place it into the Variable: box
by clicking the arrow between the two buttons.
27. Click OK.
28. Be sure to add a figure title and edit the graph so it follows APA 7 graphing
conventions. It should look similar to the following:
SAVE YOUR OUTPUT FILE
29. The output file needs to be saved as a separate file (different from the data file).
To save the output file, click on the File menu and select Save As. Just like the
data file, follow the path to your home directory in the Save in box. To save the
file, in the box next to File name: type Lab7 and then click Save. You can use
the same file name as the data file because the two files are saved with different
extensions. The output file will be saved with the .spv extension.
EXPORTING YOUR OUTPUT TO A WORD DOCUMENT
30. If you want to export your output to WORD and submitted as a Word file, follow
these instructions: With your output open, click on the File menu and select
Export . The Export Output dialogue box should appear. You will need to
change three things. 1) Under Objects to Export, select the radio button next to
All Visible (change from the default All). 2) Under Document: Type: select the
down arrow and change the format to Word/RTF file (*.doc), if necessary. 3)
Click the Browse button. The Save As dialogue box will appear. Follow the
path to your home directory in the Look in box and name the file (the default is
OUTPUT.doc). Click Save and OK. Be sure to check the Word file to make sure
the output was exported properly.
Homework
Work on your presentation and paper for Lab #8: Stairway to Heaven
7
I Will Remember You
One topic of central interest to both experimental psychologists and the public is the
accuracy of the human memory. Barlett (1932) is usually credited with conducting the
first investigations of false memories, remembrances of events that never occurred. He
studied distortions of memory using a complex prose passage. Participants read a folktale
The War of the Ghosts and tried to recall it repeatedly. Results showed that
participants memories became more and more distorted over repeated attempts to recall.
These results suggest that everyday memory is not always as reliable and faithful
reproduction of the past, a static snapshot of events as they truly were. Instead, memory is
sometimes fallible, imperfect and reconstructive, and shaped by present circumstances.
While these conclusions about the fallibility of everyday memory seem justified, it is
conceivable that memory distortion occurs only under restricted conditions. It is perhaps
not surprising that participants found it difficult to retell a story, rich and complex in
meaning, in exactly the same way. Should not some variability be expected in storytelling? Indeed, it is quite possible that Barletts participants were themselves aware that
the story was changing with repeated tellings. His findings would surely be strengthened
if it were found that participants were totally unaware of the intrusions of irrelevant
material into their story. In addition, it would be of some interest to know whether
memory distortion occurs in other paradigms, for example, serial-list learning.
In serial-list learning, the experimenter reads aloud a list of words and the participants
memorize and then later try to recall each of the presented words. The words are usually
presented one-by-one in short lists comprised of 15 or so items. The recall test involved
the participants listing, in written form, the items they can remember from the studied
list. Often, a recognition test is included. In the recognition test, the experimenter
provides a list of words, which contains items from the studied lists and lures, words
never presented. Participants indicate their level of confidence about whether each item
had occurred. The task is often made more difficult by presenting multiple lists.
Remembering words not presented, or recognizing them, would constitute a false
memory.
Common sense would suggest that remembering or recognizing words not presented
should occur with low frequency. In addition, if participants did misremember words,
they should not express high confidence that a particular misremembered word was
actually in the list. In a recognition test, for example, they may agree that a non-studied
item was probably in the list, when it was not, but they should never state with
complete assurance that they had actually heard it. And, indeed, they should be incapable
of actually recollecting the moment at which the word was read by the experimenter,
since it was never actually presented.
Procedure
Two experimenters will read prepared lists of words aloud. After each list is read,
participants will immediately write down as many words as they can remember on for 1
minute each. When all of the lists are completed, participants will be given a recognition
test, which contains studied and non-studied items. For each item, the students will rate
whether it was a) surely new, b) probably new, c) probably old, or d) surely old. If the
item was rated as surely old, participants should indicate which of the two experimenters
they remembered uttered the word.
References
Barlett, F.C. (1932). Remembering: A study in experimental and social psychology.
Cambridge University Press.
Questions
1. Answer the following questions.
a. Identify the independent variable and the levels of the independent
variable. (0.5 point)
b. Identify the dependent variable. (0.5 point)
c. Outline your theory of memory. (1 point)
d. What is the experimental hypothesis? (1 point)
2. What percentages of the studied and non-studied items were recognized as a)
surely old, b) probably old, c) probably new, and d) surely new? Break the nonstudied items into unrelated lures, weakly related lures, and critical lures. To
answer this question, present the data in a 4 x 4 APA style table with the levels of
independent variable listed in separate rows and the levels of the dependent
variable listed in separate columns. In the table, there should be four levels of
item status (studied, non-studied/unrelated lure, non-studied/weakly related lure,
and non-studied/critical lure) and four possible responses (surely old, probably
old, probably new, and surely new). (2 points)
3. Answer the following questions.
a. With regard to the critical lures, what percentage of the critical lures were
classified as surely old? (0.5 point)
b. What percentage of the participants said the critical lures were surely
old? (0.5 point)
c. What percentage of the participants that classified a critical lure as surely
old indicated they remembered which experimenter had uttered the
critical lure (a word never actually presented)? (0.5 point)
4. Do the results support the experimental hypothesis? Be sure to provide an
explanation by referring to the results. (1.5 points)
5. People often say they vividly remember the details surrounding a particular event,
which attests to the fact that memory cannot be false. What do our data have to
say about this issue? (2 points)
The following four questions are designed to get you to explore the interaction between
item relatedness (i.e., critical/related versus unrelated) and item classification (i.e., old
versus new).
6. Your instructor had provided you with a SPSS data file that has combined
categories; that is, lures classified as probably new or surely new should be
considered new and lures classified as probably old or surely old should be
considered old. Use SPSS (instructions below) to obtain the mean number of
items in each of the four categories (critical lure/new, critical lure/old, unrelated
lure/new, unrelated lure/old).
7. Use the means obtained in the previous question to produce an APA style line
graph with the mean number of items recognized along the y-axis, the type of lure
(critical or unrelated) along the x-axis, and define the lines by the classification
category (new/old). You can do this using SPSS (instructions below). (2 points)
8. Use the line graph to describe whether there is an interaction (between type of
word and classification category). (1 point)
9. Use SPSS to determine whether the interaction between type of word and
classification category is statistically significant. Describe the findings using APA
style. Use the p-value to assess statistical significance. Recall, if p-value = a,
reject H0 (result is statistically significant.) (1.5 points)
Report Preparation
Prepare a neat and tidy lab report. It is recommended that you type your lab report. Your
report should include the following:
APA style title page
SPSS output
Answers to the nine questions.
Lab Total: 14.5 points
SPSS Instructions for Analyzing Main Effects and Interactions
DATA ENTRY Your lab instructor has converted the Qualtrics data from Excel
into an SPSS file that you may download from Nexus. Instructions 1 to 9
below are associated with copying, pasting, and creating data from the Excel
spreadsheet without the Qualtrics compilation and Macros conversion of the
Excel data. You may download and open the SPSS file provided, skip
instructions 1 to 9 and begin with number 10, Create an output file.
1. On the Variable View tab of the Data Editor create three variables: lure,
classcat, and count.
Name
lure
Type
Numeric
Decimals
0
Label
Type of Lure
classcat
Numeric
0
Classification
Category
surely
probably
Numeric
Numeric
0
0
Values
1 = unrelated
2 = critical
1 = old
2 = new
2. Copy and paste the data from Excel into SPSS.
a. Copy the values from the Unstudied-Unrelated Lure SO (surely old)
column in Excel and paste them into the surely variable in SPSS. For the
lure variable enter a value of 1 and for the classcat variable enter a value
of 1.
b. Copy the values from the Unstudied-Unrelated Lure PO (probably old)
column in Excel and paste them into the probably variable in SPSS (next
to the values in the surely column from part a).
c. Copy the values from the Unstudied-Unrelated Lure PN (probably new)
column in Excel and paste them into the probably variable in SPSS (below
the values from part b). For the lure variable enter a value of 1 and for the
classcat variable enter a value of 2.
d. Copy the values from the Unstudied-Unrelated Lure SN (surely new)
column
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