Spps training presentation 1

Wednesday, January 13, 2016
JANUARY /2014JANUARY /2014

Componentsof theTraining
Overview of SPSS
SPSS for Window
Basic Information of SPSS
How to enter data in SPSS
How to import external data into SPSS
How to clean and edit data
How to transform variables
How to sort and select cases
Analysis Menu
How to get Basic Statistics Analysis
2

Overview of SPSS
It provides a powerful statistical analysis & data
management system
Can be used to analyze data from surveys, tests
observations, etc
Provides a variety of data analysis & presentations
functions,

Continuo……
Statistical analysis & graphical presentations
Descriptive statistics:- frequencies, central
tendency, plots, charts & lists
Sophisticated Inferential & multivariate
statistical procedures:-
analysis of variance (ANOVA), factor, cluster,
categorical data analysis

Overview of SPSS forwindows
•Most frequently used in analyzing data in SPSS
are the two type windows: Data Editor and Output
Viewer windows
Data Editor:- is the window that is open at start-
up and used to enter and store data in a
spreadsheet format.
Output Viewer:- opens automatically when you
execute an analysis or create a graph using dialog
box or command syntax

SPSSinterface
Data view
The place to enter data
Columns: variables
Rows: records
Variable view
The place to enter variables
List of all variables
Characteristics of all variables
6

Continuo
Output Viewer
It contains the result of all statistical analyses &
graphical displays of data windows
It contains the result of all statistical analyses &
graphical displays of data windows
Main we focus on the methods necessary for
inputting, defining and organizing data in
SPPS.

Basic Information of SPPs
Menu Bar:
The menu bar provides a series of “drop down”
commands to perform most essential SPSS
functions.
By clicking on a menu command, a further series
of menu options will appear.
File: These are the basic file management
operations. (opening, saving, and printing files
Edit: This allows you to perform editing
functions on the current data set. (cut, copy,
clear, undo changes and redo changes

View: Allows you to change the current view of data, as well
as toolbar options. (grid lines, value labels
Data: These functions deal with the configuration, defining,
and management of data. (insert variables/cases, sort data,
merge files
Transform: This allows you to transform the data set you’ve
entered. (calculating new variables, recoding, missing values
Analyze: Includes the main data analysis functions.
(descriptive statistics, t-Tests, ANOVA, correlation, data
reduction
Windows: Allows you to alter the appearance, format,
position of the SPSS windows.
Continuo

Continuo
By clicking the VARIABLE VIEW tab.
At this point the options that you might consider are as
follows:
TYPE: The default is numeric data, (it allows us to change
from numeric data to other formats.
We can change formats by clicking the cell, then clicking
the three dots in the right corner of the cell.
The most common format change is to “string” data, which
will allow you to enter words rather than numbers.

ContinuoWIDTH:-It allows us to set the maximum number of digits
(or letters in a string format)
The decimal and all decimal points count as digits in the
width.
DECIMALS :- It indicates how many decimal points you
can have in your cell.
LABELS :- we can enter a longer description of the variable
here.
VALUES:- We can tell SPSS what the values (mainly for
categorical data like gender), If We have a code of “-1”
for men and “1” for women

BeforetheDataEntry
You need a code book/scoring guide
You give ID number for each case (NOT real
identification numbers of your subjects) if you
use paper survey.
If you use online survey, you need something to
identify your cases.
You also can use Excel to do data entry.
12

Exampleof acodebook
13
A code book is about how you code your
variables. What are in code book?
1.Variable names
2.Values for each response option
3.How to recode variables

Questionnaire
Insert

Enter or Importing Data

Enter datain SPSS16.0
16
Columns:
variables
Rows: cases
Under
Data View

Enter variables
17
1. Click this
Window
1. Click Variable View
2. Type variable name under
Name column (e.g. Q01).
NOTE: Variable name can be 64
bytes long, and the first
character must be a letter or
one of the characters @, #, or
$.
3. Type: Numeric, string, etc.
4. Label: description of
variables.
2. Type
variable name
3. Type:
numeric or
string
4. Description
of variable

Enter variables
18
Based on your
code book!

Enter cases
19
Under Data
View
1. Two variables in the data set.
2. They are: Code and Q01.
3. Code is an ID variable, used to identify individual
case (NOT people’s real IDs).
4. Q01 is about participants’ ages: 1 = 12 years or
younger, 2 = 13 years, 3 = 14 years…

Import datafrom Excel
Select File Open Data
Choose Excel as file type
Select the file you want to import
Then click Open
20

Import datafrom CVSfile
CVS is a comma-separated values file.
If you use Qualtrics to collect data (online
survey), you will get a CVS data file.
Select File Open Data
Choose All files as file type
Select the file you want to import
Then click Open
22

Continue
29
Save this
file as SPSS
data

Clean dataafter import datafiles
Key in values and labels for each variable
Run frequency for each variable
Check outputs to see if you have variables with
wrong values, or missing values and physical
surveys if you use paper surveys
Sometimes, you need to recode string variables
into numeric variables
30

Continue……
31
Wrong
entries

Variabletransformation
Recode variables
32
1. Select Transform Recode
into Different Variables
2. Select variable that you want
to transform (e.g. Q20): we
want
1= Yes and 0 = No
3. Click Arrow button to put
your variable into the right
window
4. Under Output Variable: type
name for new variable and
label, then click Change
5. Click Old and New Values

Continue…..
6. Type 1 under Old Value
and 1 under New Value,
click Add. Then type 2
under Old Value, and 0
under New Value, click
Add.
7. Click Continue after
finish all the changes.
8. Click Ok
33

Continue…..
Compute variables
Example 3: Convert string variable into
numeric variable
34
1. Enter 1 at Numeric
Expression.
2. Click If button and
type Q2 = ‘Female’
3. Then click Ok.
4. Enter 2 at Numeric
Expression.
5. Click If button and
type Q2 = ‘Male’
6. Then click Ok

Sort and select cases
Sort cases by variables: Data Sort Cases
You can use Sort Cases to find missing.
35

Variable Measurement Level
Measurement levels are nominal, scale & ordinal,
You can specify the level of measurement as
 Scale (numeric data on an interval or ratio scale),
ordinal, or nominal.
Nominal and ordinal data can be either string
(alphanumeric) or numeric.

Continuo ……
Nominal:- a variable can be treated as nominal
when its values represent categories with no
intrinsic ranking .
For example:- department of the company in
which an employee works,
 It include region, zip code, and religious
affiliation.

Continuo ……
Ordinal:- A variable can be treated as ordinal
when its values represent categories with some
intrinsic ranking
 For example:- levels of service satisfaction from
highly dissatisfied to highly satisfied;
 It include attitude scores representing degree of
satisfaction or confidence and preference rating
scores.

Continuo ……
Scale:- A variable can be treated as scale when its
values represent ordered categories with a
meaningful metric,
 So that distance comparisons between values
are appropriate.
Examples of scale variables include age in years
and income in thousands of birr.

Continuo …..
Note: For ordinal string variables, the alphabetic
order of string values is assumed to reflect the
true order of the categories.
For example, for a string variable with the values
of low, medium & high
The order of the categories is interpreted as high,
low, medium, which is not the correct order.
In general, it is more reliable to use numeric
codes to represent ordinal data.

Continuo …….
New numeric variables created during a session
are assigned the scale measurement level.
For data read from external file formats and SPSS
data files that were created prior to version 8.0,
default assignment of measurement level is
based on the following rules:
Numeric variables with fewer than 24 unique
values and string variables are set to nominal.
 Numeric variables with 24 or more unique
values are set to scale.

ANALAYSEMENU
Reports
We can choose one or more of the following
subgroup statistics for the summary variables
within each category of each grouping variable:-
 Sum, number of cases, mean, median, grouped
median
 Standard error of the mean, minimum,
maximum, range, variable value of the first or
last category of the grouping variableWednesday, January 13, 2016

Continuo …….
 Standard deviation, variance, kurtosis, standard
error of kurtosis, skewness, standard error of
skewness, percentage of total cases,
 Percentage of total sum, percentage of total
cases within grouping variables
 Percentage of total sum within grouping
variables, geometric mean, and harmonic mean.

Continuo …….
 We can change the order in which the subgroup
statistics appear.
 The order in which the statistics appear in the
Cell Statistics list is the order in which they are
displayed in the output.
 Summary statistics are also displayed for each
variable across all categories.

Basic statistical analysis
Descriptive statistics
Purposes:
1.Find wrong entries
2.Have basic knowledge about the sample and
targeted variables in a study
3.Summarize data
Analyze Descriptive statistics Frequency
45

Continuo …….
First: - Displays the first data value encountered in the
data file.
 Geometric Mean: - The nth root of the product of
the data values, where n represents the number of
cases.
 Grouped Median: - Median that is calculated for
data that is coded into groups. Grouped median is
the median calculated from the coded data.
For example, with age data, if each value in the 30s is
coded 35, each value in the 40s is coded 45, and soWednesday, January 13, 2016

Continuo …….
 Harmonic Mean: - Used to estimate an average
group size when the sample sizes in the groups
are not equal.
Kurtosis: - A measure of the extent to which
observations cluster around a central point. For a
normal distribution, the value of the kurtosis
statistic is zero.
Positive kurtosis indicates that the observations
cluster more and have longer tails than those in
the normal distribution, and
Negative kurtosis indicates that the observations
cluster less and have shorter tails.

Kurtosis: A measure of the extent to which
observations cluster around a central point.
For a normal distribution, the value of the
kurtosis statistic is zero.
Leptokurtic data values are more peaked,
whereas
platykurtic data values are flatter and more
dispersed along the X axis.

Continuo …….
Last:- Displays the last data value encountered in
the data file.
Maximum:-The largest value of a numeric
variable.
Mean:- A measure of central tendency. The
arithmetic average, the sum divided by the
number of cases.
Median: - The value above and below which half
of the cases fall, the 50th percentile.Wednesday, January 13, 2016

Continuo …….
If there is an even number of cases, the median is
the average of the two middle cases when they
are sorted in ascending or descending order.
Minimum: - The smallest value of a numeric
variable.

 N. The number of cases (observations or
records).

Continuo …….
Percent of N in: - Percentage of the number of
cases for the specified grouping variable within
categories of other grouping variables.
 If you only have one grouping variable, this
value is identical to percentage of total number
of cases.
 Percent of Total N:-Percentage of the total
number of cases in each category.

Continuo …….
Percent of Sum in: - Percentage of the sum for
the specified grouping variable within categories
of other grouping variables.
 If you only have one grouping variable, this
value is identical to percentage of total sum
 Percent of Total Sum: - Percentage of the total
sum in each category.

Continuo …….
Range: - The difference between the largest and
smallest values of a numeric variable, the
maximum minus the minimum.
 Skewness: - A measure of the asymmetry of a
distribution. The normal distribution is
symmetric and has a skewness value of 0.

Continuo …….
 A distribution with a significant positive
skewness has a long right tail
A distribution with a significant negative
skewness has a long left tail.
As a guideline, a skewness value more than
twice its standard error is taken to indicate a
departure from symmetry.

Skewness: a measure of the asymmetry of a
distribution. The normal distribution is
symmetric and has a skewness value of
zero.
Positive skewness: a long right tail. Negative
skewness: a long left tail.
Departure from symmetry : a skewness value
more than twice its standard error.

Continuo …….
 Standard Deviation: - A measure of dispersion
around the mean.
In a normal distribution, 68% of cases fall within
one standard deviation of the mean and 95% of
cases fall within two standard deviations.
For example, if the mean age is 45, with a
standard deviation of 10, 68% and 95% of the
cases would be between -------------- in a normal
distribution.

Continuo …….
Standard Error of Kurtosis: - The ratio of
kurtosis to its standard error can be used as a test
of normality (that is, you can reject normality if
the ratio is less than -2 or greater than +2).
A large positive value for kurtosis indicates that
the tails of the distribution are longer than those
of a normal distribution;
A negative value for kurtosis indicates shorter
tails (becoming like those of a box-shaped
uniform distribution)

Continuo …….
 Standard Error of Mean: - A measure of how
much the value of the mean may vary from
sample to sample taken from the same
distribution.
 It can be used to roughly compare the observed
mean to a hypothesized value (that is, you can
conclude the two values are different if the ratio
of the difference to the standard error is less than
-2 or greater than +2).

Continuo …….
Standard Error of Skewness: - The ratio of
skewness to its standard error can be used as a
test of normality (that is, you can reject normality
if the ratio is less than -2 or greater than +2).
 A large positive value for skewness indicates a
long right tail;
An extreme negative value indicates a long left
tail.

Continuo …….
Sum: - The sum or total of the values, across all
cases with non missing values.
 Variance: - A measure of dispersion around the
mean, equal to the sum of squared deviations
from the mean divided by one less than the
number of cases.
 The variance is measured in units that are the
square of those of the variable itself.

THANK YOU FOR YOUR
ATTENTATION

Spps training presentation 1

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