SPSS I
Course Instructor Guide
Outline:
In Detail:
i.
Statistical Package for the Social Sciences
i.
Basic Terms
1. Case
2. Variables
a. Nominal
b. Ordinal
c. Interval
d. Ratio
3. Values
4. Normal
Distribution
5. Standard
deviation
6. Analysis
a. One-Sample
T-Test
b. One-Way
ANOVA
c. Correlation
7. It
is expected that you have a grasp of these
i.
There is not enough time to cover both statistics and
the program
i.
If a window appears asking, What
would you like to do?
1. Select
a. Type
in Data
b. OK
ii.
Toolbars
1. Cover
toolbars
i.
You are currently in the SPSS Data Editor
ii.
Spreadsheet-type layout
1. Columns
and rows
2. Headings
3. Row
numbers (no value to these numbers)
4. Use
arrow keys to move from cell to cell
iii.
Type in data and name variables (two ways to type in)
1. After
typing in a number hit enter
a. 1-3,
then, 1,1,1, then 87-92
|
1 |
1 |
87 |
|
2 |
1 |
53 |
|
3 |
1 |
92 |
2. Type
a number then hit tab to complete the row
|
4 |
1 |
70 |
|
5 |
1 |
78 |
iv.
Coding
1. SPSS
is a quantitative analysis program
a. Works
with numbers
b. We
try to convert text to code
i.
Gender
1. F
= 1
2. M
= 2
v.
Show how to delete
1. Rows
2. Columns
3. Data
i.
Choose bottom left tab, Variable View
ii.
Name
1. Variable
names can only be between 1-8 characters
2. Any
combination of numbers and letters, but must begin with a letter
3. Name
variables as: student, gender, and score
iii.
Decimals
1. Change
all to 0
iv.
Label
1. More
description of the field
2. score
a. Midterm
Score
v.
Values
1. Code
Information
a. Click
the button to the right of the text box
i.
Value, 1
ii.
Value Label, Female
iii.
Value, 2
iv.
Value Label, Male
vi.
Go back to Data View
i.
15 men and 15 women in an introductory psychology class
have taken their midterms
ii.
In this example, we wish to construct frequency
distributions and obtain some basic descriptive statistics for the variables gender
and score
|
Student |
Gender |
Score |
|
1 |
1 |
87 |
|
2 |
1 |
53 |
|
3 |
1 |
92 |
|
4 |
1 |
70 |
|
5 |
1 |
78 |
|
6 |
1 |
73 |
|
7 |
1 |
91 |
|
8 |
1 |
60 |
|
9 |
1 |
77 |
|
10 |
1 |
82 |
|
11 |
1 |
85 |
|
12 |
1 |
33 |
|
13 |
1 |
88 |
|
14 |
1 |
98 |
|
15 |
1 |
88 |
|
16 |
2 |
89 |
|
17 |
2 |
73 |
|
18 |
2 |
91 |
|
19 |
2 |
76 |
|
20 |
2 |
75 |
|
21 |
2 |
89 |
|
22 |
2 |
81 |
|
23 |
2 |
83 |
|
24 |
2 |
68 |
|
25 |
2 |
86 |
|
26 |
2 |
55 |
|
27 |
2 |
89 |
|
28 |
2 |
89 |
|
29 |
2 |
70 |
|
30 |
2 |
93 |
i.
On the menu toolbar choose Analyze > Descriptive Statistics > Frequencies
1. Move
the variables from the left to the right box
2. After
choosing which variables to use always check what options or preferences are
available before choosing OK
a. Move
gender and score
b. Check the Display Frequency Tables box
c. Choose
Statistics
i.
Check all boxes for dispersion, central
tendency, and distribution
ii.
Click continue
d. Choose
Charts
i.
Choose Histogram,
with
ii.
Choose Continue,
and OK
e. Choose Format
i.
Leave alone
f.
Click Continue,
and OK
i.
The data file is the .sav
file
ii.
The output file is the .spo
file
i.
Look on the desktop at the two files
i.
Discuss the right and left window views
ii.
Briefly discuss
1. Each
table
2. Both
Histograms
i.
Choose SPSS
Chart Object > Open
1. Now in a third window
a. Run
through the following
i.
The chart
options button
ii.
The line style button
iii.
Label style
iv.
The text button
v.
Select the columns (chart series), and use the color button
2. Close
the window
a. The
change takes place in the output file
i.
In the SPSS I folder choose iqexample.sav
i.
The principal of the
ii.
In this problem we are testing the null hypothesis that
the mean IQ of all school children in the
i.
Choose Analyze
> Compare means > One-Sample T Test
1. Move
IQ to the box labeled Test Variables
ii.
Then, click the box labeled Test Value
1. Enter
105
iii.
Check Options
1. Confidence
Interval 95%
2. Exclude
cases analysis by analysis
iv.
Click OK
v.
In the output file, examine the results
1. Is
a mean difference of 5.73 large enough to be significantly different 105? The results of the t-test show that t=3.900,
with 29 (N-1) degrees of freedom. The
two-tailed p-value for this result is .001.
The result is considered statistically significant if the p-value is
less than the chosen alpha level usually .05 (and .01), so the result is
considered statistically significant and the null hypothesis is rejected
i.
The SFSU psychology department conducted a study to
determine the effectiveness of an integrated / experimental methods course as
opposed to the traditional method of taking the two courses separately. It was hypothesized that combining the two
would be better. To determine whether
there actually was a difference in student performance as a result of
integrated versus separate training; the final research projects of 20 students
from an integrated course and 20 students from the traditional course were
evaluated. There scores are listed in this
file.
ii.
In this problem we are testing the null hypothesis that
there is no difference in student performance as a result of the integrated
versus traditional courses, that is, that the mean difference between the
conditions in the population from which the sample was drawn is zero.