Analyzing Data. Learning Objectives You will learn to: – Import from excel – Add, move, recode, label, and compute variables – Perform descriptive analyses.

Slides:



Advertisements
Similar presentations
Data Analysis using SPSS By Dr. Shaik Shaffi Ahamed Ph. D
Advertisements

Hypothesis testing 5th - 9th December 2011, Rome.
By Hui Bian Office for Faculty Excellence Spring
Kruskal Wallis and the Friedman Test.
Advance to next slide1 Interactive Introduction to SPSS Statistical Software Elizabeth Bigham, Ph.D. California State University San Marcos May
Independent t -test Features: One Independent Variable Two Groups, or Levels of the Independent Variable Independent Samples (Between-Groups): the two.
©2004, 2006, 2008 UIW Department of Instructional Technology Meat and Potatoes SPSS Presented by Terence Peak.
Analysis of variance (ANOVA)-the General Linear Model (GLM)
Copyright © Allyn & Bacon (2007) Using SPSS for Windows Graziano and Raulin Research Methods This multimedia product and its contents are protected under.
Introduction to SPSS Allen Risley Academic Technology Services, CSUSM
Basic Data Analysis for Quantitative Research
By Wendiann Sethi Spring  The second stages of using SPSS is data analysis. We will review descriptive statistics and then move onto other methods.
1 An Introduction to IBM SPSS PSY450 Experimental Psychology Dr. Dwight Hennessy.
QM Spring 2002 Business Statistics SPSS: A Summary & Review.
A Simple Guide to Using SPSS© for Windows
Introduction to SPSS Descriptive Statistics. Introduction to SPSS Statistics Program for the Social Sciences (SPSS) Commonly used statistical software.
Introduction to SPSS Short Courses Last created (Feb, 2008) Kentaka Aruga.
Questionnaire Development Part II: SPSS, Reliability, and Validity Personality Lab October 11, 2010.
Repeated Measures ANOVA Used when the research design contains one factor on which participants are measured more than twice (dependent, or within- groups.
Computing our example  Step 1: compute sums of squares  Recall our data… KNR 445 Statistics ANOVA (1w) Slide 1 TV MovieSoap OperaInfomercial
SW388R7 Data Analysis & Computers II Slide 1 Analyzing Missing Data Introduction Problems Using Scripts.
Statistics for the Social Sciences Psychology 340 Fall 2013 Thursday, November 21 Review for Exam #4.
Inferential Statistics: SPSS
LEARNING PROGRAMME Hypothesis testing Intermediate Training in Quantitative Analysis Bangkok November 2007.
SPSS Series 1: ANOVA and Factorial ANOVA
By Hui Bian Office for Faculty Excellence 1. K-group between-subjects MANOVA with SPSS Factorial between-subjects MANOVA with SPSS How to interpret SPSS.
Advance to next slide1 Set Up Module Section 1. Advance to next slide2 Interactive Introduction to SPSS Statistical Software Elizabeth Bigham, Ph.D. California.
Srinivasulu Rajendran Centre for the Study of Regional Development (CSRD) Jawaharlal Nehru University (JNU) New Delhi India
Using SPSS for Windows Part II Jie Chen Ph.D. Phone: /6/20151.
Questionnaire Development: SPSS and Reliability Personality Lab October 8, 2010.
Social Science Research Design and Statistics, 2/e Alfred P. Rovai, Jason D. Baker, and Michael K. Ponton Entering Data Manually PowerPoint Prepared by.
Hypothesis testing Intermediate Food Security Analysis Training Rome, July 2010.
Work with Variables Section 5. Add a variable Click on the top grey portion of the GPA column to highlight the column. At the top left of your screen,
SPSS Basics and Applications Workshop: Introduction to Statistics Using SPSS.
1 Analysis of Variance ANOVA COMM Fall, 2008 Nan Yu.
What is SPSS  SPSS is a program software used for statistical analysis.  Statistical Package for Social Sciences.
Developed By Information Technology Services University Of Saskatchewan.
Recap of data analysis and procedures Food Security Indicators Training Bangkok January 2009.
1 An Introduction to SPSS for Windows Jie Chen Ph.D. 6/4/20161.
Perform Descriptive Statistics Section 6. Descriptive Statistics Descriptive statistics describe the status of variables. How you describe the status.
ANOVA: Analysis of Variance.
Smoking Data The investigation was based on examining the effectiveness of smoking cessation programs among heavy smokers who are also recovering alcoholics.
Mr. Magdi Morsi Statistician Department of Research and Studies, MOH
1. Tables, Charts, and Graphs Microsoft Word & Excel 2003.
Review of Factorial ANOVA, correlations and reliability tests COMM Fall, 2007 Nan Yu.
Understanding SPSS Brandon Aragon, Research Technician Eric Cazares, Graduate Assistant Claudia Alvarado, Graduate Assistant Workshop Series October.
PSC 47410: Data Analysis Workshop  What’s the purpose of this exercise?  The workshop’s research questions:  Who supports war in America?  How consistent.
Conduct Simple Correlations Section 7. Correlation –A Pearson correlation analyzes relationships between parametric, linear (interval or ratio which are.
DTC Quantitative Methods Summary of some SPSS commands Weeks 1 & 2, January 2012.
PSY6010: Statistics, Psychometrics and Research Design Professor Leora Lawton Spring 2007 Wednesdays 7-10 PM Room 204.
Social Science Research Design and Statistics, 2/e Alfred P. Rovai, Jason D. Baker, and Michael K. Ponton Between Subjects Analysis of Variance PowerPoint.
Mixed Models ANOVA Within-Subjects & Between-Subjects Chapter 14.
1 PEER Session 02/04/15. 2  Multiple good data management software options exist – quantitative (e.g., SPSS), qualitative (e.g, atlas.ti), mixed (e.g.,
Understanding SPSS Workshop Series February 18, 2016.
If sig is less than 0.05 (A) then the test is significant at 95% confidence (B) then the test is significant at 90% confidence (C) then the test is significant.
CHAPTER 15: THE NUTS AND BOLTS OF USING STATISTICS.
Workshop Series May 17, 2017 Brandon Aragon
Introduction to the SPSS Interface
Introduction to SPSS July 28, :00-4:00 pm 112A Stright Hall
Dr. Siti Nor Binti Yaacob
By Dr. Madhukar H. Dalvi Nagindas Khandwala college
Just the basics: Learning about the essential steps to do some simple things in SPSS Larkin Lamarche.
DEPARTMENT OF COMPUTER SCIENCE
Dr. Siti Nor Binti Yaacob
Data Entry and Managment
SPSS STATISTICAL PACKAGE FOR SOCIAL SCIENCES
Hypothesis Testing and Comparing Two Proportions
Hypothesis Testing Part 2: Categorical variables
By A.Arul Xavier Department of mathematics
Introduction to the SPSS Interface
Presentation transcript:

Analyzing Data

Learning Objectives You will learn to: – Import from excel – Add, move, recode, label, and compute variables – Perform descriptive analyses – Conduct simple correlations – Test reliability of measures – Conduct t-tests – Use syntax

/ Open Excel file: CurlyStraightStudy.xls

Create Meaningful Variable Labels Simple – Easily read by SPSS/PASW Distinct – Meaningful to you, and easy to distinguish from other variables.

Find and Replace in Excel Convert “String” Variables into Numeric Variables. Replace “999” or other missing data codes with blanks.

Show a classmate your completed Excel file

Download Excel file: computer science data.xls

Open SPSS/PASW by going to Start > All Programs

User Interface

Importing from Excel* Open an existing data source by clicking “Okay” (or click cancel and go to File > Open) Navigate to Excel file (file must be closed) - use drop down to select “.xls” files Select “toSPSS” worksheet with one click and then select “OK”

Main Window

Three windows in SPSS/PASW* 1.Main window – what you see now Data View – rows of data, like excel; one subject per row Variable View - where you see and edit information about your variables; one variable per row 2.Output window – after you run an analysis 3.Syntax – recording analyses

Output Window Output gets added to the file - can select and delete unnecessary output Save your output

Syntax Window Allows you to save your code for future use In SPSS dialog boxes, click “Paste” instead of “OK” Select and hit Ctrl-R to run syntax Use “*” to comment out – end comments with a “.”

Prepping Data in SPSS/PASW

Descriptive Statistics* Describe the characteristics of individual variables – Frequencies for categorical* variables Analyze > Descriptive Statistics > Frequencies – Means and standard deviation for continuous* variables Analyze > Descriptive Statistics > Descriptives How would you find out how many males and females you have? *Other names you might have heard: Continuous = Interval; Categorical = Discrete

Descriptive Statistics* Describe the characteristics of individual variables – Split by group Data > Split File> Compare Groups – Compare means and standard deviation for continuous* variables by Condition, Gender, etc. How would you find out the average age of each gender and the average overall age? *Other names you might have heard: Continuous = Interval; Categorical = Discrete

Recoding Variables* To group participants together based on their answers, you need to recode their answers Transform > Recode > Into Different Variables Highlight “year” move it into the box Type “year_r” in Name > Change

Recoding Variables* Click on Old and New Values In Old Value, type Freshman In New Value, type 1 Click Add Repeat for Sophomore (1), Junior (2), Senior (2)

Recoding Variables In Data View, scroll over to the right and you will see your new variable How would you label the values so you know what 1 and 2 means?

Labeling variable names In Variable view: g o to the Label column and type more descriptive name

Labeling variable values* In Variable view: label gender values with “male” and “female” – Click on grey box in Values column – Enter 1 for Value and Male for Label; repeat for 2 = Female In Data View: View > Value Labels

Computations in SPSS/PASW

Correlation A Pearson correlation computes relationships between continuous variables

Analyze > Correlate > Bivariate Can enter several variables to get a matrix of relationships Correlation*

if the p-value (“Sig.”) is less than.05, then the relationship between the two are significant There is a positive correlation between number of programming classes and reported likelihood of majoring in computer science, r(5) =.96, p <.05.

Assessing reliability* To figure out if two+ dvs “hang together”, select Analyze > Scale > Reliability Analysis In Items, enter the variables you would like to collapse across Click Statistics and check the Scale if Item Deleted box

Computing new variables* To do computation involving one or more variables, select Transform > Compute In Target Variable, type new variable name (weightedgpa) In Numeric Expression, type computation (MEAN(curentgpa, majorgpa)

Analyzing Data in SPSS/PASW

T-test* A t-test compares the means of two groups to each other Analyze > Compare Means > Independent samples t-test Which gender reports being more likely to major in computer science?

T-test* Click on Define Groups and put M and F in Groups 1 and 2

T-test* Women and men report being equally likely to major in computer science, t(3) = -1.63, ns.

What test you should use* Are your data continuous? If yes Do you have two groups to compare to each other? If yes Are your groups independent (between) or dependent (within)? If independent Independent samples t-test! If dependent Paired samples t-test!

* What kind of DV? Continuous What kind of IV(s)? Continuous# of IVs?OneCorrelationTwo +RegressionCategorical# of IVs?OneLevels of IV?Two Within-subjects or between-subjects? Paired samples t-test Independent samples t-test Three + One-way ANOVA Two + Within-subjects or between subjects? ANOVA (GLM Univariate) ANOVA (GLM Repeated Measures) Categorical What kind of IV(s)? Continuous Logistic regression Categorical Chi squared test What Test to Use

One way ANOVA (one IV but 3 levels ) Analyze  compare means  One-way ANOVA Next screen: – Dependent List: (your DV) – Factor: (your IV) Post hoc  Tukey (where groups differed) Options  Descriptives Looks at whether you have a statistically significant different between groups

Using SPSS syntax Allows you to save your code for future use In SPSS dialog boxes, click “Paste” instead of “OK” Select and hit Ctrl-R to run syntax Use “*” to comment out – end comments with a “.”

Selecting subjects* Data > Select Cases > Click “If…”

Selecting subjects* In box, type the criteria you want (gender = “M”) Use Boolean logic (&, |, ~=, ANY()) String variables needs quotes around their values To select everyone, go back to Data > Select Cases and select “All Cases”

Congratulations! You have learned how to – Import data into SPSS/PASW – Label variables and their values – Recode and compute new variables – Obtain frequencies and other descriptive statistics – Run a correlation – Test for reliability – Run a t-test – Run a 2x2 ANOVA – Use syntax

Project HW this Week (due Sunday 5pm) Should finish collecting you own project data by end of this week

Project HW this Week (due Sunday 5pm) Excel data template with 20+ subjects entered, ready for SPSS import – Logsheet entered separately – Freeze panes – No text in numeric fields – Variables named appropriately

This Wednesday Finish SPSS analysis and output – Group activity Time to work on Lab HW