spssintrotr

8/9/2019 SPSSintrotr

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Introduction to SPSS


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Object of the Course

• About the four-windows in SPSS

• The basics of managing data files

• The basic analysis in SPSS


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Introduction: What is SPSS?

• SPSS (Statistical Product and Service Solutions)is a statistical software that enables us to perform

statistical procedures easily, quickly and

accurately.

• SPSS has four windows:

Data editor

Output viewer

Syntax editorScript window

• Today, we will use only two of them.


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• Data EditorSpreadsheet-like system for defining, entering, editing,

and displaying data. Extension of the saved file will be“.sav”


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• Output Viewer

Displays output and errors. Extension of the saved file willbe “.spv”


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The basics of managing

data files


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Opening SPSS

• Start → All Programs → IBM SPSS Statistics → → IBMSPSS Statistics 20


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The first time you run SPSS, the following window will appear.

You can chose one of the given options there. In the meantime click Cancel.

Opening SPSS


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Opening SPSS

• The default window will have the data editor

• There are two sheets in the window:

1. Data view 2. Variable view


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Data View window

This sheet is visible when you first open the Data Editor andthis sheet contains the data

It has two views: Data view and Variable view

Click


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Variable View window

• This sheet contains information about the data set that is stored

with the dataset • Name

– The first character of the variable name must be alphabetic

– Variable names must be unique, and have to be less than 64characters.

– Spaces are NOT allowed.


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Variable View window: Type

• Type

– Click on the ‘type’ box. The two basic types of variablesthat you will use are numeric and string.

This column

enables you to specify the type of variable.


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Variable View window: Width

• Width

– Width allows you to determine the number ofcharacters SPSS will allow to be entered for thevariable


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Variable View window: Decimals

• Decimals – Number of decimals

– It has to be less than or equal to 16

3.14159265


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Variable View window: Label

• Label

– You can specify the details of the variable

– You can write characters with spaces up to 256

characters


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Variable View window: Values

• Values

– This is used and to suggest which

numbers represent which categories when

the variable represents a category


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Defining the value labels

• Click the cell in the values column as shown below

• For the value, and the label, you can put up to 60

characters.

• After defining the values click add and then click OK.

Click


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Practice 1

• How would you put the following information into

SPSS?

Value = 1 represents Male and Value = 2 represents Female

Name Gender Height

JAUNITA 2 5.4SALLY 2 5.3

DONNA 2 5.6

SABRINA 2 5.7

JOHN 1 5.7

MARK 1 6ERIC 1 6.4

BRUCE 1 5.9


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Practice 1 (Solution Sample)

Click


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Click


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Saving the data

• To save the data file you created simply click ‘file’ and

click ‘save as.’ You can save the file in different forms

by clicking “Save as type.”

Click


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Sorting the data

• Click ‘Data’ and then click Sort Cases


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Sorting the data (cont’d)

• Double Click ‘Name of the students.’ Then clickok.

Click

Click


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Practice 2

• How would you sort the data by the‘Height’ of students in descending order?

• Answer

– Click data, sort cases, double click ‘height of

students,’ click ‘descending,’ and finally clickok.


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Transforming data

• Click ‘Transform’ and then click ‘Compute Variable…’


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Transforming data (cont’d)

• Example: Adding a new variable named ‘lnheight’ which is

the natural log of height

– Type in lnheight in the ‘Target Variable’ box. Then type in

‘ln(height)’ in the ‘Numeric Expression’ box. Click OK

Click


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Transforming data (cont’d)

• A new variable ‘lnheight’ is added to the table


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Practice 3

• Create a new variable named “sqrtheight”which is the square root of height.

• Answer


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• Frequencies – This analysis produces frequency tables

showing frequency counts and percentagesof the values of individual variables.

• Descriptives

– This analysis shows the maximum, minimum,mean, and standard deviation of the variables

• Linear regression analysis

– Linear Regression estimates the coefficientsof the linear equation

The basic analysis


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Opening the sample data

• Open ‘Employee data.sav’ from the SPSS


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Opening the sample data

• Go to “File,” “Open,” and Click Data• Go to Program Files,” “SPSSInc,” “IBMStatistics,”

and “Samples” folder.

• Open “Employee Data.sav” file


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Frequencies

• Click ‘Analyze,’ ‘Descriptive statistics,’ then

click ‘Frequencies’


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Frequencies

• Click gender and put it into the variable box.

• Click ‘Charts.’

• Then click ‘Bar charts’ and click ‘Continue.’

Click Click


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Frequencies

• Finally Click OK in the Frequencies box.

Click


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Using the Syntax editor

• Click ‘Analyze,’ ‘Descriptive statistics,’ thenclick ‘Frequencies.’

• Put ‘Gender’ in the Variable(s) box.

• Then click ‘Charts,’ ‘Bar charts,’ and click

‘Continue.’ • Click ‘Paste.’

Click


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Using the Syntax editor

• Highlight the commands in the Syntax editorand then click the run icon.

• You can do the same thing by right clicking the

highlighted area and then by clicking ‘Run

Current’

ClickRightClick!


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Practice 4

• Do a frequency analysis on the variable“minority”

• Create pie charts for it

• Do the same analysis using the syntax

editor


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Answer

Click


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Descriptives

• Click ‘Analyze,’ ‘Descriptive statistics,’ thenclick ‘Descriptives’

• Click ‘Educational level’ and ‘Beginning

Salary,’ and put it into the variable box.

• Click Options

Click


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Descriptives

• The options allows you to analyze otherdescriptive statistics besides the mean and Std.

• Click ‘variance’ and ‘kurtosis’

• Finally click ‘Continue’

Click

Click


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Descriptives

• Finally Click OK in the Descriptives box. You willbe able to see the result of the analysis.


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Normal Distribution

I) Area under the normal distribution (CDF)

Example: Find the area to the left of 1 in thestandard normal distribution.

Example: Suppose that the scores in a Stat

course follows a normal distribution with mean70 and a standard deviation 10. Find the

percentage of scores less than 78.

Transform Compute CDF & Noncentral

CDF


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Normal Distribution

II) The inverse function for the normal distribution

Example: Find the 20th percentile in the previousexample.

Transform Compute Inverse DF


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Testing Hypothesis

I) One sample T-Test

Example: In order to determine the number of

workers required to meet demand, the

productivity of newly hired trainees is studied. It

is believed that trainees can process and

distribute more than 450 packages per hour

within one week of hiring. Can we conclude that

this belief is correct, based on productivity

observation of 50 trainees, See worksheet

“Productivity”.


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Analyze Compare Means One-Sample T-Test

1) The hypotheses are:

H0:m ≤ 450 and Ha: m > 450

2) Assumptions: we have large sample (n=50)

3) t=1.894) P-value=0.065=0.0323

5) Since 0.0323 < .05, we reject H0. The

trainees can process and distribute more

than 450 packages per hour within one weekof hiring.


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Analyze

Compare Means

One-Sample T-Test

Confidence Intervals

Test value should be zero

Click Options to set confidence level.

In the previous example, calculate 95% for

the true mean of the number of packages

that trainees can process and distribute perhour within one week of hiring.


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Regression Analysis

• Click ‘Analyze,’ ‘Regression,’ then click

‘Linear’ from the main menu.


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Regression Analysis

• For example let’s analyze the model• Put ‘Beginning Salary’ as Dependent and ‘Educational Level’ as

Independent.

edusalbegin 10

ClickClick


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Regression Analysis

• Clicking OK gives the result


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Practice 5

• Find out whether or not the previousexperience of workers has any affect

on their beginning salary?

– Take the variable “salbegin,” and“prevexp” as dependent and independent

variables respectively.

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