SPSS WORKSHOP - PowerPoint PPT Presentation

1 / 59
About This Presentation
Title:

SPSS WORKSHOP

Description:

Analyze and Graphs are used to create output. Tabs (bottom left hand corner of data editor) ... a new data file. Now we are going to open up a data set. File ... – PowerPoint PPT presentation

Number of Views:59
Avg rating:3.0/5.0
Slides: 60
Provided by: clow9
Category:

less

Transcript and Presenter's Notes

Title: SPSS WORKSHOP


1
? SPSS WORKSHOP ?
  • Please Log onto Your Computer Station
  • User Name type in your user ID
  • Password type in your password
  • Domain ASUAD
  • If you have trouble signing in
  • Then try signing in with westguest account
  • User Name westguest
  • Password asuwest
  • Domain (this computer)
  • Sometime after todays class, please go to
    Technopolis (basement of library) to get your
    user ID fixed.

2
Laptops
  • You can move the laptop to where ever you want to
    sit.
  • If the laptop gives you a warning that the
    battery is running low, we have extra laptops you
    can switch with.
  • If the laptops are not frequently used then they
    will go to sleep. So please move your mouse
    every few minutes.
  • If the laptops happen to fall asleep (or shut
    down),
  • please push the power button, which is located at
    top left hand corner of your keyboard.
  • Then you will have to retype in the password.
  • There is a sign in sheet going around the room
    for the laptops. Each lap top has a unique
    identification number located behind the screen.
    Please put your name next to the laptop you are
    using

3
Workshop IIDescriptive Statistics with SPSS
  • Roger Berger
  • Mathematical Sciences
  • Applied Computing Department
  • Gaurav Jaju
  • Melissa Wilson
  • Statistics Laboratory

http//www.west.asu.edu/StatLab
4
Workshop II Overview (p. 1)
  • Function of Stat Lab
  • Review of basic function of SPSS Data Editor
  • Complete survey and enter data
  • Brief review of how variables were edited in
    variable view
  • Creating Composites
  • Descriptive statistics
  • Level of measurement
  • Summarizing distributions of variables
  • Central tendency and variability (dispersion)
  • Comparing means between samples
  • Relationships ? (will not be covered for this
    workshop)
  • Correlations
  • Stat Lab resources
  • Online resources survey design
  • Our reference library

5
Open up your internet Explorer
  • http//www.west.asu.edu/StatLab
  • Click on Workshops
  • Click on Data used for SPSS Workshops
  • Click on Fin_Health_SWG693
  • Please save it in your Desktop.
  • Close the internet browser.

6
SPSS Accessibility (p. 3)
  • Network access
  • Technopolis (basement of library)
  • Desktop (hard drive) installed
  • Computer Classrooms
  • Stat Lab
  • Software versions can be purchased at the
    Computer Store (or Bookstore)
  • Student Edition (SE) (has limitations). 95.00
  • Grad Pak (has much more features)
  • (version 14 15)
  • 209.00
  • only graduate students can get it
  • Can download price list from http//bookstore.asu
    .edu/

7
Accessing the Statistic Laboratory
  • Location CLCC 107
  • Phone (602) 543-6117
  • Website http//www.west.asu.edu/StatLab
  • Operating hours See website
  • When using the lab, please sign in at the front
    counter

8
Support for Statistics (p. 4)
  • Function of Stat Lab (also pp. 5-7)
  • The Stat Lab staff assists students with aspects
    of statistical software.
  • The lab is not set up to consult on methodology
    (survey design, procedure design) or
    interpretation of the results.
  • The Stat Lab is not set up to provide one-on-one
    tutorial service for students on a regular basis.
  • However, we have and frequently do answer general
    statistic questions.
  • In essence, we are set up to help with the
    statistical software.
  • Statistics Tutoring (especially for statistic
    courses)
  • Learning Enhancement Center
  • TRiO (SSS) program

9
Overview of the Research Process
Page 8
DISCUSSION SECTION
Interpretation Were the hypotheses supported?
Why or why not? Any limitations? What are
the Implications? Suggestions for further
research?
RESULTS SECTION
Data Analysis Descriptive Statistics Inferential
Statistics
METHODS SECTION
Measures or Instruments Validity - What did we
measure? Reliability How precise was the
measure? Data Analytic Approach Which
type of data analyses were conducted?
METHODS SECTION
Participant Characteristics Who did you
sample? Procedures How did we do the
observations?
AT THE END OF LITERATURE REVIEW OR INTRODUCTION
Based on theory literature review, what is
(are) the question(s) you want to address? Do
males and females have different attitudes? Do
participants in different age groups have
different attitudes? Will a research methods
course (intervention) increase students attitudes
to research?
Research Consulting Center Statistics Lab CLCC
107 www.west.asu.edu/rcc (602) 543-6117
10
Please fill out the survey (Remove the last page
of your handout)
  • Response
  • Strongly Disagree
  • Disagree
  • Agree
  • Strongly Agree
  • Sex
  • Male
  • Female
  • Age
  • Response
  • Strongly Disagree 1
  • Disagree 2
  • Agree 3
  • Strongly Agree 4
  • Sex
  • Male 1
  • Female 2
  • Age
  • Actual age in years
  • Having ID column will help you keep track of
    cases
  • What do the 1st five questions measure?
  • What do the 2nd five questions measure?

11
Open up your internet Explorer
  • http//www.west.asu.edu/StatLab
  • Click on Workshops
  • Click on Data used for SPSS Workshops
  • Click on Fin_Health_SWG693
  • Please save it in your Desktop.
  • Close the internet browser.

12
Please launch SPSSthen Turn to Page 10 of Handout
  • Menu Bar
  • Data Transform are used to manipulate the data
    in data editor (i.e., spread sheet)
  • Analyze and Graphs are used to create output
  • Tabs (bottom left hand corner of data editor)
  • Data View (top panel)
  • Columns Variables (e.g., questions on survey)
  • Rows Cases (e.g., survey)
  • Variable View (bottom panel)
  • How we edit the variables
  • Give variables their names, labels, etc

13
Open a new data file
  • Now we are going to open up a data set.
  • File gt open gt Data
  • Navigate to your desktop
  • Open up the data file that you downloaded from
    our website.

14
Variable View
  • Click on Variable View
  • Tab (located lower left hand corner)
  • Pages 12 13 of your handout
  • Variable Name
  • Numeric
  • Width
  • Decimal
  • Variable Label
  • Value Label
  • Missing
  • Column
  • Align
  • Measure

15
Variable View
  • Variable View
  • Tab (located lower left hand corner)
  • Pages 12 13 of your handout
  • Variable Name
  • Numeric
  • Width
  • Decimal
  • Variable Label
  • Value Label
  • Missing
  • Column
  • Align
  • Measure

16
Overview of Next Section of Workshop
  • Transforming Variables
  • (computing composite scores)
  • Descriptive Statistics
  • Central Tendency
  • Dispersion (Variability)
  • Presentation of Data tables figures
  • Comparing Means
  • Relationships ? may not be covered in workshop
  • Correlations
  • Other information in packet

17
Transforming Variable (p 14)
  • Recode
  • Data may be need to be recoded for a variety of
    reasons
  • Examples
  • Common for reversing the scales
  • Converting a continuous variable into discrete
    ordinal variable
  • Transform gt Recode gt Into Different Variables
  • Computing a New Variable
  • Can create new variables that may be a function
    of pre-existing variables
  • Transform gt Compute
  • Instead of clicking ok, you have the option of
    clicking on the paste button.
  • The paste button pastes the command language in a
    syntax file. (This will be discussed shortly)

18
Transforming Variable (p 14)
  • Recode
  • Data may need to be recoded for a variety of
    reasons
  • Examples
  • Common for reversing the scales
  • Converting a continuous variable into discrete
    ordinal variable
  • Transform gt Recode gt Into Different Variables
  • Computing a New Variable
  • Can create new variables that may be a function
    of pre-existing variables
  • Transform gt Compute

19
Thanks for having us ?We will see you next week.
  • Do keep the Research Attitudinal Survey you
    filled out.
  • Please bring back your packets next week.
  • Please close SPSS log off your computer.
  • Please turn in the SPSS Workshop Evaluation as
    you leave the room.

Have a good day. ?
20
Financial Stability Composite Scale
  • Person A has extremely low financial stability.
  • How do you think he would answer questions f01
    through f05?
  • SD D A SA?
  • However, person B owns a very profitable
    business.
  • How do you think she would answer items f01
    through f05 ?
  • SD D A SA?

21
Financial Stability Composite Scale
22
Financial Stability Composite Scale
23
Financial Stability Composite Scale
24
Financial Stability Composite Scale
25
Financial Stability Composite Scale
26
Financial Stability Composite Scale
27
Health Service Accessibility Composite Scale
  • What if person B also has high Health Service
    Accessibility ?
  • She has great medical benefits and can get free
    services from her sisters medical practice
  • How do you think she would answer the Access to
    Health Service questions?

28
Health Service Accessibility Composite Scale
29
Health Service AccessibilityComposite Scale
30
Health Service AccessibilityComposite Scale
31
Reverse Scoring
  • What is the reverse scores for h10?

revh10
h10
1 2 3 4
4 3 2 1
? ? ? ?
32
Look at the SPSS in data view
  • What is the variable called revh10?
  • Reverse of h10
  • "cannot get the medicines I need" with scoring
    reversed.
  • What is the variable finance?
  • Finance Composite sum(f01,f02,f03,f04,f05)
  • Construct Financial Stability
  • What is the variable health?
  • Heath Composite sum(h06,h07,h08,h09,revh10)
  • Construct Accessibility to Health Services

33
Syntax command language (p15)
  • A syntax file is simply a text file that contains
    commands.
  • SPSS provides a powerful command language that
    allows you to save and automate many common
    tasks.
  • The command language also allows you to save your
    jobs in a syntax file so that you can repeat your
    analysis at a later date
  • While it is possible to open a syntax window and
    type in commands, it is often easier if you let
    the software help you build your syntax file
  • Instead of clicking OK, you can click on Paste

34
When should you use Syntax?
  • You want to keep a record of what you did
  • When you are still collecting data
  • Intervention research pre post
  • You have quite a bit of composite scores to
    create
  • When you are repeating a type of analyses over
    and over again.

35
Syntax File (optional)
  • When you click on paste, a new window, called
    syntax, appears.
  • The command language is copied onto the syntax
    file.
  • If you highlight the language and click on run
    or on the arrow button, the command file will be
    executed

36
Syntax File (optional)
  • Sometimes it is helpful to organize the syntax
    file by typing in notes.
  • So that SPSS wont read the notes as command, you
    should type in asterisks preceding your notes.
  • For example,
  • Scoring for finance variables
  • Make sure there is a space between your notes and
    the commands
  • After commands have been created (or pasted),
    make sure you put in a space after the commands
  • that way, additional commands will be pasted a
    line below the previous commands.
  • After you are done doing a set of functions or
    the same type of analyses, dont forget to save,
    name, and close the syntax file
  • You may want to name the file relating to the
    type of commands it is doing.
  • For example, scoring.

37
Lets Create a Composite Score
  • The following will be in supplemental handout
    (page 3)
  • Make sure that you are in data view tab
  • Click on Transform gt Compute

38
(No Transcript)
39
(No Transcript)
40
(No Transcript)
41
(No Transcript)
42
(No Transcript)
43
(No Transcript)
44
(No Transcript)
45
(No Transcript)
46
(No Transcript)
47
Overview Analyzing Data Creating Graphs
  • Level of Measurement
  • Descriptive Analysis
  • Presentation of Data
  • Central Tendency Variability

48
What are the Levels of Measurement? (p. 16)
Ratio
SPSS calls them scale
  • (e.g., income, costs, frequency counts
    number of people, capacities, rates)
  • Different categories
  • Rankable categories
  • Constant equal-sized Intervals
  • Absolute Zero (physical significance) (e.g.,
    temperature in Kelvin, time)
  • construct a meaningful fraction (or ratio) with a
    ratio variable

Interval
  • (e.g.., scales financial stability,
    age, temperature in fahrenheit or celicuis)
  • Different Rankable categories
  • Constant equal-sized Intervals
  • can be expressed numerically
  • the distance between attributes does have meaning
  • No absolute zero

Ordinal
  • (e.g.., education attainment, class
    status)
  • Different Categories
  • Categories are rankable (attributes can be
    rank-ordered)
  • Intervals are NOT equal-sized
  • Is the distance between 1 and 2, the same as
    between 3 and 4?
  • Distances between attributes do not have any
    meaning.
  • We don't assume a value of 2 means that HS
    degree are twice something than less than HS.

Nominal
  • (e.g.., sex, ethnicity, agency,
    location)
  • Different Categories
  • numerical values just "name" the attribute
    uniquely
  • NOT Rankable
  • We don't assume that higher values mean "more" of
    something and lower numbers signify "less".

49
Temperature Example
Kelvin is a temperature scale designed so that
zero degrees K is defined as absolute zero (all
molecular movement stops and all actual
temperatures are above absolute zero)
50
Descriptive Statistics
  • Presentation of entire distribution
  • Frequency Distribution organized tabulation of
    the number (or percentage) of individuals in each
    category on the scale of measurement
  • Can be presented in a table or in a graph
  • Measures of Central Tendency
  • Identifies a single score that represents an
    entire data set
  • Best example of average or most typical score
  • Measures of Variability (Dispersion)
  • Provides a description of how spread out the
    scores are in a distribution
  • Provides a measure of how accurately a single
    score selected from a distribution represents the
    entire set

51
Presentation of entire distribution of a
variable(page 16)
52
Central Tendency and Dispersion
53
Central Tendency and Dispersion
54
Back to SPSS
  • Create table frequency a chart
  • Create measures of central tendency
  • Create measures of dispersion

55
How can we summarize the distribution of the
below variable?
  • Gender
  • Male
  • Female

What is the level of measurement? (see page 16,
1st slide)
Nominal
Should we use a bar graph or a histogram? (see
page 16, 2nd slide)
Bar Graph
56
Presentation of an Nominal Variable
  • Click Analyze gt click Descriptive Statistics gt
    then click Frequencies.
  • You should see a dialog box called Frequencies.
  • On the left side you should see a list of
    variables and on the right you should see a
    Variable(s) box.
  • In the variable list (left side) look for a
    variable either called Gender or sex.
  • Select this variable by clicking on it, then
    click ?to place the variable in the Variable(s)
    box.
  • Make sure that there is a check mark next to
    Display frequency tables.
  • Click Charts.
  • You will see a dialog box called Frequencies
    Charts
  • Click Bar Charts. Click Continue.
  • Click OK.

57
(No Transcript)
58
(No Transcript)
59
Dialogue box called Frequencies
60
(No Transcript)
61
Frequency and Percentage Distribution of Gender
(N96)
Missing Cases 2
62
(No Transcript)
63
We want to know the central tendency for the
below variables. (p 18)
  • Age of respondent
  • 18 89. Actual age in years

What is the level of measurement?
Which measure of central tendency should we use?
(see page 16, 3rd slide)
64
Central Tendency Variability for Interval
Ratio Variable
  • Click Analyze gt click Descriptive Statistics gt
    then click Descriptive.
  • You will see a dialog box called Descriptives.
  • Select the variable
  • one is called AGE.
  • Click Options. You will see a dialog box called
    Descriptives Options
  • By default Mean, Std Deviation, Minimum,
    Maximum should be selected
  • click Continue.
  • Click OK.

65
Mean and Standard Deviation of Age (N96)
66
Mean Comparisons
  • Back to the supplemental handout (page 4)
  • Lets say we want to see if males and females
    differ in their financial stability.
  • In SPSS we can compare the mean financial
    stability between gender categories

67
Mean Comparison
68
Mean Comparison
  • The left side contains the list of variables from
    the data set.
  • You can scroll down to find the two variables
  • Sex (gender) and Financial Stability.
  • After choosing a variable you can move it into
    one of the boxes on the right.
  • Dependent List
  • Independent List
  • Which variable is the dependent variable? Sex or
    Financial Stability?
  • Which variable is the independent variable?

69
Mean Comparison
70
Mean Comparison
71
Mean Comparison Output Window
72
Mean Comparison Output
73
Summary of what we have discussed.
  • Presentation of the variable distributions
  • Central tendency
  • Variability (dispersion)
  • Comparing means across groups

74
Inferential Statistics (p 19)
  • Techniques that allow us to study samples and
    then make generalizations about the population
    from which they were selected.
  • Sample a set of individuals selected from a
    population, usually intended to represent the
    population in a research study.
  • Population The collection of all individuals
    (cases) in which the researcher is interested.

75
Statistical Significance
  • Statistical Significance (probability)
  • Probability is used to predict what kind of
    samples are likely to be obtained from a
    population.
  • Probability establishes a connection between
    populations and samples
  • Relying on this connection, inferences of
    populations can based on sample statistics

76
Research Question
  • Actual research is conducted using a sample
  • Hypothesis test a statistical method that uses
    sample data to evaluate a hypothesis about a
    population parameter.
  • Hypotheses are stated in terms of population
    parameters
  • Research Hypotheses, for example,
  • There is a relationship between age financial
    stability.
  • There is an financial differences between males
    and females (i.e., There is an gender effect on
    financial stability)
  • There is a change or a difference between pre and
    post test scores

77
Research Questions the Applicable Statistical
Procedures
  • Relationships
  • Chi-square
  • Correlation
  • Regression
  • Differences between 2 sample means
  • Independent samples
  • Independent t-test
  • Dependent samples
  • Paired-sample t-test
  • Differences among 2 or more independent sample
    means
  • Analysis of Variance (ANOVA)

78
Relationship
  • Often, science involves a search for
    relationships between variables. For example, is
    there is a relationship between the amount of
    rainfall and crop growth?
  • Sometimes, it is reasonable to expect a
    consistent, orderly relation between two
    variables As X changes, Y also changes in a
    predictable way.

79
Linear Relationships with SPSS
  • Two options
  • Regression Analysis
  • Analyze gt Regression gt Linear
  • Correlation Coefficient (simpler)
  • Analyze gt Correlate gt Bivariate
  • Scatter Plot
  • Graphs gt Scatter gt Simple ...

80
Correlations
  • Click on Analyze
  • click on correlate
  • Click on bivariate
  • Find variable Financial Stability
  • Move it to the right
  • Find variable Age
  • Move it to the right
  • We have to choose Pearson or Spearman rho
  • Pearson correlation is appropriate when two
    variables are continuous (interval and variable)
  • Spearman rho correlation is appropriate when at
    least one of the variables are ordinal (the other
    variable can be continuous or ordinal)

81
Correlation
82
Scatter Plot Example of a Positive Relationship

83
Creating a contingency table and computing a
chi-square (?2)
84
Creating a contingency table and calculating a ?2
  • Choose Chi-square
  • Put one of the variables in Row(s) and the other
    variable in Column(s)
  • Click on button called Statistics

85
Contingency Table and Chi-Square
86
Two Sample t Tests with SPSS
  • Independent-Samples t Test (Sex res_pre)
  • Analyze gt Compare Means gt Independent-Samples T
    Test
  • t test
  • If p lt .05 then significant
  • Paired-Samples t Test (usually for pre post
    test)
  • Analyze gt Compare Means gt Paired-Samples T Tests
  • t test
  • If p lt .05 then significant

87
Independent-Samples t Test Output
88
Paired-Samples t Test Output
89
Differences among 2 or more independent sample
means with SPSS
  • Analysis of Variance
  • Analyze gt Compare Means gt One-Way ANOVA
  • F test
  • If p lt .05 then significant

90
Helpful Pages in Your Packet
  • APA Outline of Empirical Research Paper (pp 5-7)
  • SPSS Statistics Cheat Sheet (pp 23-24)
  • Printing Output (p26)
  • Print Preview
  • You can print only part of the output, by first
    selecting (single clicking) a particular output
  • Sometimes you may want to set up the page as
    landscape before printing
  • AFS network Space (p 27)
  • Backing up your files to your server space via
    internet

91
Stat Lab Resources
  • 12 PC computers, printer (free printing), and
    copier (limited use)
  • Office supplies (stapler, 3-hole puncher, paper
    clips)
  • Reference library (books can not leave the Stat
    Lab)
  • Introductory text books on Statistics Research
    Methods
  • Publication manual of the American Psychological
    Association
  • Presenting your findings a practical guide for
    creating tables
  • Displaying your findings a practical guide for
    creating figures, posters, and presentations
  • Using SPSS for Windows Macintosh analyzing
    understanding data analyses (helpful in
    interpreting the results and writing it in APA
    format)

92
Review of Workshop
  • Overview of Research Process
  • Introduction to SPSS
  • Input importing raw data
  • Editing raw data
  • Transforming reversing items and creating
    composite scores
  • Introduction to the Syntax File
  • Analyzing Data Create Graphs with SPSS
  • Descriptive Statistics Level of Measurement
  • Central Tendency
  • Dispersion
  • Presentation of Data tables figures
  • Comparing means between samples
  • Stating Hypotheses
  • Relationships
  • Two sample t-tests Independent Paired
  • ANOVA

93
Review of Workshop
  • Overview of Research Process
  • Introduction to SPSS
  • Input importing raw data
  • Editing raw data
  • Transforming creating composite scores
  • Analyzing Data Create Graphs with SPSS
  • Level of Measurement Descriptive Statistics
  • Central Tendency
  • Dispersion
  • Presentation of Data tables figures
  • Comparing Means across groups (e.g., gender)
  • Correlations

94
Thanks for having us as your guests ?
  • We have to justify the Stat Lab conducting SPSS
    workshops.
  • Could you please fill out the SPSS workshop
    Evaluation at last page of the packet.
  • For question 4 please circle not apply
  • If would please write comments about
  • what you like most of the workshop,
  • what you have learned about the workshop,
  • how we may be able to improve it.
  • We will greatly appreciate it.
  • Thank You,

95
Thanks for having us as your guests ?
  • Do keep the Research and Statistics
    Attitude Survey you filled out.
  • Please turn in the SPSS Workshop
    Evaluation. You can drop off this evaluation
    near the door, or at front table.
  • Please come and visit
  • the Stat Lab (CLCC 107)

Have a good day. ?
96
Thanks for having us ?
  • Do keep the Financial and Health Attitude
    Survey you filled out.
  • Please close SPSS log off your laptop. If
    the laptop logged you off or automatically shut
    off, please turn back on and put in your password
    so that the computer can be properly shutdown.
  • However, please turn in the SPSS Workshop
    Evaluation 2. After you have completed the
    survey please come up and leave the survey by the
    front table or desk.
  • Your professor may still need to continue with
    class, so please dont leave yet.
  • Please come and visit the Stat Lab (CLCC 107).

Have a good day. ?
97
Thanks for having us ?
  • Do keep the Financial and Health Attitude
    Survey you filled out.
  • Please close SPSS log off your computer.
  • Your professor may still need to continue with
    class, so please dont leave yet.
  • However, please turn in the SPSS Workshop
    Evaluation 2. After you have completed the
    survey please come up and leave the survey by the
    front table or desk.
  • Please come and visit the Stat Lab (CLCC 107).

Have a good day. ?
Write a Comment
User Comments (0)
About PowerShow.com