Rosseni Din
Muhammad Faisal Kamarul Zaman
Nurainshah Abdul Mutalib
Why?
 To describe the sample
 To check the assumption
 To address specific research questions
How?
 Frequencies
 Descriptives
 Explore
Frequencies
 Categorical variables
 E.g.
 Male vs Female
Descriptives
 Continous variables
 Provides:
 Mean
 Median
 Standard deviation
 Provides info on distribution of scores
 Skewness
 Kurtosis
 Searching for missing data
Normality
 Symmetrical, bell-shaped curve
 Greatest frequencies in the middle and smaller are
toward the extreme
 Obtained by skewness and kurtosis values
 Histogram can also be used
Outliers
 Histogram
 Look at the tails of the distribution
 Boxplot
 Look at the little circles with number attached
 Check whether it is an error or not
Descriptive Statistic
Descriptive statistic used to give a systematic general
idea using Frequency, Mean and others.
This test is only used to report frequencies and
percentages involved in the researches conducted. The
steps are:
1.
Click Analyze, Descriptive Statistics and choose Frequency
2. This will be displayed:
3. Move the variables that you want to look at the
frequencies
4. Click Charts and choose any tye of charts that you
wanted to use, then click ok
5. This will be the result:
6. Or like this:
7. Maybe like this:
Data normality test
in general, it is used for inferential statistic. The
procedures are:
1.
Click Analyze, Descriptive Statistics and choose
EXPLORE.
2. Choose the variable that you want and then move
them to Dependent List box
3. in Label Cases by box, put your independent
Variable
4. In Display, make sure both (Dependent dan
Independent) is chosen.
5. For Statistic choices, choose Descriptive and
Outliers
6. for Plot, under descriptive, choose Histogram. click
Normality Plots with test. Then click Continue
7. For Option, in Missing Value section, choose Exclude
Cases pairwaise. Click continue then OK
8. The output will be like this:
Tests of Normality
Kolmogorov-Smirnova
variabel.x
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
0.159
249
0.000
.948
249
0.000
a. Lilliefors Significance Correction
for Kolmogorof- Smirnov table, we are given information about
data normality value. When the value shows non signifikan value
( value > 0.05) this shows that the data is normal
To look for OUTLIERS
from the normality test procedures , we can also
look for outliers in our data. This can be done using
Boxplot. It is shown in small circle with number
outside the boxplot as shown in the next slide:
Example of data that have outliers
In this case, there are 2 data which is categorized as outliers which is
respondent number 177 dan 117. in order to eliminate them we need to go back and
delete this 2 data.
Money Isn’t an Issue!
Topics With Parents
Relative % Frequency
Everything
45%
Academics
29%
Social Life
17%
Lets Parents Talk
6%
Money
3%
Total
100%
Only
3%
of
students talk with their
parents about money. Are
USD students that well
off?
Do you value
YOUR LIFE?
Times With
Drunk Driver
Relative %
Frequency
Cumulative %
Frequency
10+
26%
26%
7-9
5%
31%
4-6
11%
42%
1-3
18%
60%
0
40%
100%
Total
100%
100%
60%
of USD
students have gotten inside a car
with a drunk driver.
What does this say about our
respect for life?
Normal is the New Skinny
Number of Breakfasts
Weight
0-1
2-3
4-5
6-7
Under
0%
11%
11%
6%
Normal
71%
89%
68%
80%
Over
29%
0%
21%
14%
Grand Total
100%
100%
100%
100%
Of the students that eat 0 or 1 breakfast a
week,
0%
are under weight.
Ironically, the under weight eat.
Car or Education:
What’s More Important?
Car Price Compared to Scholarship Received
$60,000
$50,000
$40,000
USD
$30,000
Scholarship
$20,000
R² = 0.0579
$10,000
$0
$0
$10,000
$20,000
$30,000
$40,000
$50,000
Car Price
The less money received for an
education, the more money spent
on a vehicle.
$60,000
Money,
Money,
Money
USD Scholarship
Distribution
45%
42%
40%
35%
30%
Relative %
Frequency
25%
20%
20%
15%
15%
USD’s tuition is $200,000
for four years.
42%
of students are paying
without assistance for an
education that they could
spend on a Ferrari.
10%
6%
8%
9%
5%
0%
0
0.1-10000
10001-20000 20001-30000 30001-40000
USD Scholarship (Dollars)
40001 +
Will we live in a virtual
reality?
USD students spend
90
minutes on
social networks a day.
How will future
generations learn
to socialize?
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
1.530256
0.133201
1.5
2
1.073897
1.153254
9.889534
2.31316
7
0
7
99.46667
65
Hands-on exercise
 Use survey3ED.sav from
www.allenandunwin.com/spss
 OR
 http://rosseni.wordpress.com/2011/07/15/spss-for-
beginners/
Procedure for Creating a bar graph
1. Graphs > Legacy Dialogs > Bar > Clustered
2. In Data in Chart are section, click on Summaries for
groups of cases > click Define
3. In the Bars represent box click Other summaries
function - click on the continuous variable of interest
(e.g. total perceived stress). Click on the arrow button
The variable should appear in the box listed as Mean
(Total Perceived Stress). This indicates that the mean on the Perceived Stress
Scale for the different groups will be displayed
Procedure for Creating a bargraph
4. Click on your first categorical variable (eg agegp3).
Click on the arrow button to move it into the Category
Axis box. This variable will appear across the bottom
of your bar graph (x axis).
5. Click on another categorical variable (eg sex). Click
on the arrow button to move it into the Define clusters
by: box. This variable will be represented in the
legend
6. OK