1 Analyzing and interpreting data Matt Calvert, UW-Extension Youth Development Specialist PDAC Wisline Web February 5, 2009 “There’s a world of difference.

Slides:



Advertisements
Similar presentations
Quantitative and Scientific Reasoning Standard n Students must demonstrate the math skills needed to enter the working world right out of high school or.
Advertisements

1 Analyzing quantitative data. 2 Things aren’t always what we think! Six blind men go to observe an elephant. One feels the side and thinks the elephant.
COLLECTING DATA ON A SAMPLE OF RESPONDENTS Designing survey instruments.
How do I summarize and make sense of all these words?
1 Making Sense of Evaluation Data Mary Michaud, MPP University of Wisconsin— Cooperative Extension Fall 2002.
INTERPRET MARKETING INFORMATION TO TEST HYPOTHESES AND/OR TO RESOLVE ISSUES. INDICATOR 3.05.
Historical Research.
Introduction to Qualitative Research
Introduction to research Analyzing and interpreting research data
Methodology Tips for Constructing Instruments. Matching methods to research paradigm MethodQuantitativeQualitative Written Instrument Standardized Instrument.
Washington State Prevention Summit Analyzing and Preparing Data for Outcome-Based Evaluation Using the Assigned Measures and the PBPS Outcomes Report.
1 © 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation Collecting Data This is STEP 3 of the five steps.
University of Wisconsin - Extension, Cooperative Extension, Program Development and Evaluation Unit 6: Analyzing and interpreting data “There’s a world.
Creating Research proposal. What is a Marketing or Business Research Proposal? “A plan that offers ideas for conducting research”. “A marketing research.
Quantifying Data.
Analytical Thinking.
1 Qualitative Evaluation Terms Coding/categorization The process of condensing qualitative data through the identification of common themes. Data Matrix.
Business and Management Research
Today Wrap up data collection Open-ended questionnaires Practice interviewing Data analysis methods How to write a chapter 3 Group time to work on project.
The Research Process Interpretivist Positivist
Preparing for Data Collection Need to recognize that data collection is a high level activity that cannot be just passed off to graduate assistant Need.
Questionnaires and Interviews
Data Analysis for Evaluation Eric Graig, Ph.D.. Slide 2 Innovation Network, Inc. Purpose of this Training To increase your skills in analysis and interpretation.
McGraw-Hill © 2006 The McGraw-Hill Companies, Inc. All rights reserved. The Nature of Research Chapter One.
School Counselors Doing Action Research Jay Carey and Carey Dimmitt Center for School Counseling Outcome Research UMass Amherst CT Guidance Leaders March.
RESEARCH A systematic quest for undiscovered truth A way of thinking
By: Christopher Prewitt & Deirdre Huston.  When doing any project it is important to know as much information about the project and the views of everyone.
Action Research March 12, 2012 Data Collection. Qualities of Data Collection  Generalizability – not necessary; goal is to improve school or classroom.
Research Methods in Computer Science Lecture: Quantitative and Qualitative Data Analysis | Department of Science | Interactive Graphics System.
Evaluation Basics Principles of Evaluation Keeping in mind the basic principles for program and evaluation success, leaders of youth programs can begin.
NorthSky Nonprofit Network Creating Customer Satisfaction Surveys Presented by Christine A. Ameen, Ed.D. Ameen Consulting & Associates
RESEARCH IN MATH EDUCATION-3
Qualitative Methods to Assess Community Issues. What are qualitative methods of assessment? Qualitative methods of assessment are those whose results.
Chapter 11: Qualitative and Mixed-Method Research Design
Dr. Engr. Sami ur Rahman Quantitative and Qualitative Data Analysis Lecture 1: Introduction.
Behavioral Research Chapter 6-Observing Behavior.
Observation & Analysis. Observation Field Research In the fields of social science, psychology and medicine, amongst others, observational study is an.
Statistical analysis Bryan NG. Pitfalls to avoid Complex analysis and big words impress people. Analysis comes at the end when there is data to analyze.
Thoughts on the Role of Surveys and Qualitative Methods in Evaluating Health IT National Resource Center for HIT 2005 AHRQ Annual Conference for Patient.
Introduction to research methods 10/26/2004 Xiangming Mu.
Quantitative and Qualitative Approaches
September 2007 Survey Development Rita O'Sullivan Evaluation, Assessment, & Policy Connections (EvAP) School of Education, University of North Carolina-Chapel.
Data Analysis. Types of Validity Internal validity degree to which results are true for the participants External validity degree to which results can.
Research Seminars in IT in Education (MIT6003) Quantitative Educational Research Design 2 Dr Jacky Pow.
Experimental Research Methods in Language Learning Chapter 9 Descriptive Statistics.
1 © 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation How do I summarize and make sense of all these words?
QUANTITATIVE RESEARCH Presented by SANIA IQBAL M.Ed Course Instructor SIR RASOOL BUKSH RAISANI.
Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.
Marketing Research Approaches. Research Approaches Observational Research Ethnographic Research Survey Research Experimental Research.
1 © 2009 University of Wisconsin-Extension, Cooperative Extension, Program Development and Evaluation Planning your evaluation This presentation provides.
Study Design Research Methods Professional Development Institute Kali Trzesniewski December 4, 2015.
Paper III Qualitative research methodology.  Qualitative research is designed to reveal a specific target audience’s range of behavior and the perceptions.
1 An Evaluation Plan and Tool Kit for the Archibald Bush Innovative Teaching and Technology Strategies Grant Valerie Ruhe and J.D. Walker, Center for Teaching.
Program Evaluation for Nonprofit Professionals Unit 4: Analysis, Reporting and Use.
LSS 2533 Research Methods. Research V Quantitative Closed data Closed data Mixed Methods Qualitative Open data.
Session 6: Data Flow, Data Management, and Data Quality.
CHAPTER ONE: INTRODUCTION TO ACTION RESEARCH CONNECTING THEORY TO PRACTICE IMPROVING EDUCATIONAL PRACTICE EMPOWERING TEACHERS.
IF GIRLS AREN’T INTERESTED IN COMPUTING CAN WE CHANGE THEIR MINDS? Julie Fisher Monash University, Melbourne, Australia,
MT320 Presented by Gillian Coote Martin. Steps to Data Analysis Start with a PlanStart with a Plan Collect and Clean Your DataCollect and Clean Your Data.
 Two types of analysis based on the data that is generated.  Quantitative or  Qualitative  Basic descriptive statistics such as mean, median, and.
Building Capacity in Evaluating Outcomes Unit 6: Analyzing and interpreting data 1 “There’s a world of difference between truth and facts. Facts can obscure.
Research Concepts 1 Approaches and Methods
Qualitative and Quantitative Data
Finding Answers through Data Collection
Office of Education Improvement and Innovation
Unit 6: Analyzing and interpreting data
UNIVERSITY OF NIGERIA, NSUKKA SCHOOL OF POSTGRADUATE STUDIES
1 Analyzing and interpreting data Matt Calvert, UW-Extension Youth Development Specialist PDAC Wisline Web February 5, 2009 “There’s a world of difference.
Business and Management Research
Ass. Prof. Dr. Mogeeb Mosleh
Presentation transcript:

1 Analyzing and interpreting data Matt Calvert, UW-Extension Youth Development Specialist PDAC Wisline Web February 5, 2009 “There’s a world of difference between truth and facts. Facts can obscure the truth.” - Maya Angelou

2 True or False? Complex analysis impresses people. I am generally able to analyze and interpret the program data I gather

3 Data analysis and interpretation Think about analysis EARLY Start with a plan Code, enter, clean Analyze Interpret Reflect –What did we learn? –What conclusions can we draw? –What are our recommendations? –What are the limitations of our analysis?

4 Why do I need an analysis plan? To make sure the questions and your data collection instrument will get the information you want. To align your desired “report” with the results of analysis and interpretation. To improve reliability--consistent measures over time.

5 Key components of a data analysis plan Purpose of the evaluation Questions What you hope to learn from the question Analysis technique How data will be presented

6 Analyzing and Interpreting Quantitative Data Quantitative Data is Presented in a numerical format Collected in a standardized manner e.g. surveys, closed-ended interviews, tests Analyzed using statistical techniques

7 True or False? Quantitative data we gather in Extension are more generalizable than qualitative data. Stating limitations weakens the evaluation

8 Analyzing Survey Data Do you want to report… how many people answered a, b, c, d? the average number or score? a change in score between two points in time? how people compared? how many people reached a certain level?

9 Common descriptive statistics Count (frequencies) Percentage Mean Mode Median Range Standard deviation Variance Ranking

10 Other Statistics Statistical Significance Factor Analysis Etc. Not often used in Extension program evaluation—generally require randomization, large samples, and/or control groups

11 Getting your data ready Assign a unique identifier Organize and keep all forms (questionnaires, interviews, testimonials) Check for completeness and accuracy Remove those that are incomplete or do not make sense

12 Data entry You can enter your data –By hand –By computer for-Analyzing-Survey-Questionnaires- P1030C0.aspxhttp://learningstore.uwex.edu/Using-Excel- for-Analyzing-Survey-Questionnaires- P1030C0.aspx

13 Data entry by computer By Computer –Excel (spreadsheet) –Microsoft Access (database mngt) –Quantitative analysis: SPSS (statistical software) –Qualitative analysis: Epi info (CDC data management and analysis program: In ViVo, etc.

14 Data entry computer screen Survey ID Q1 Do you smoke? Q2 AgeQ3 Support ordinance? Smoking: 1 (YES) 2 (NO)

15 Dig deeper Did different groups show different results? Were there findings that surprised you? Are there things you don’t understand very well – further study needed?

16 Supports restaurant ordinance Opposes restaurant ordinance Undecided/ declined to comment Current smokers (n=55) 8 (15% of smokers) 33 (60% of smokers) 14 (25% of smokers) Non-smokers (n=200) 170 (86% of non- smokers) 16 (8% of non- smokers) 12 (6% of non- smokers) Total (N=255) 178 (70% of all respondents) 49 (19% of all respondents) 26 (11% of all respondents)

17 Pre-post or post-then-pre Data Check data—any individual not responding to both pre and post should be discarded Decide: –Report individual change or combined change? –Compare to a standard? See PD&E Evaluation Quick Tip 30

18 Interpretation of Pre/Post Data Which statement is the most significant to you? The number of club officers reporting strong or very strong knowledge of parliamentary procedure increased from 4 (50%) to 6 (75%). The number of club officers reporting at least some knowledge of parliamentary procedure increased from 5 (63%) to 8 (100%). 50% of the 8 participants reported an increase in their knowledge of parliamentary procedure. Self-reports of knowledge of parliamentary procedure on a scale from 1=minimal to 4=very strong averaged before the training and 3.0 after. Rate your knowledge of parliamentary procedure : 1=minimal 2=some 3=strong 4=very strong RespondentPre-Post- A12 B33 C44 D44 E23 F13 G12 H2(missing) I3 J33

19 Discussing limitations Written reports: Be explicit about your limitations Oral reports: Be prepared to discuss limitations Be honest about limitations Know the claims you cannot make –Do not claim causation without a true experimental design –Do not generalize to the population without random sample and quality administration (e.g., <60% response rate on a survey)

20 Analyzing and Interpreting Qualitative Data Qualitative data is thick in detail and description. Data often in a narrative format Data often collected by observation, open- ended interviewing, document review Analysis often emphasizes understanding phenomena as they exist, not following pre- determined hypotheses

21 Quiz Data have their own meaning Qualitative analysis is easier than quantitative analysis

22 Analyzing qualitative data “Content analysis” steps: 1.Transcribe data (if audio taped) 2.Read transcripts 3.Highlight quotes and note why important 4.Code quotes according to margin notes 5.Sort quotes into coded groups (themes) 6.Interpret patterns in quotes 7.Describe these patterns

23 Hand coding qualitative data

24 Emergent or pre-conceived categories? Consider this section—what themes emerge related to arts and communications programs?

25 Focus group sample Q. How are the arts/comm. Activities different from other projects? When I was little, fair was never that exciting to me. I didn’t realize how much else there was to do. It’s shown me how many different things you could do and get money for it, so you can’t go wrong. Art projects are more personal. It’s more of an expression of yourself. Where with an animal, you just show the animal off. With art, you show you can do something good. (lots of agreement with this). Q. What about A&C helps with communication? You’re forced into the situations. A lot of clubs require demonstrations. The first year, everyone encouraged me just to talk. To have someone push you along the way helps. In a 4-H Club, you get to be friends. It’s more like family. If you’re ticked off at your family, you can go up to your room and draw. Feel better. It feels more comfortable because you’re not the only one. People at school say, “she’s an arts nerd.” You can relate to them. And even they’re so diverse. You cram people in and say you’ve got to get along. With school, you only go part of the year. With 4-H, it’s all year a few times a month. At school, it’s every single day. It’s too much. Q. How have you been changed? Entering art in fair has made me not worry so much about what other people think about my work. I’ll take into consideration what they say, but most of it’s opinion. They can have their own style through photography and I can have mine through sketching. I think it depends on the suggestion. I usually consider it a lot and it might help me or it might not. It’s always there in the back of your mind at least. It’s your own style. If people say, you could change this, I can say thank you for your input, but I’m not worried. Q. How is 4-H different from other school and community experiences? Working with people from all over the state and bring their ideas back. Also, how they’re doing the Madison cow parade. I wouldn’t have even heard about that. This year I have one of the micro-cows that was selected. School is an assignment. You have to do that project. Where 4-H you can do any kind of art, any way you want to do it. But at school, you can also exhibit. You can get opinions from an art teacher like from a judge. It’s not that different except that you can do what you want. Although you do learn a lot of techniques from school that you might not learn from 4-H.

26 Using theories and categories Consider this section again—how are arts and communication programs providing the 4 Essential Elements? –Generosity Opportunity to value and practice service for others –Belonging An inclusive environment and safe environment –Independence Opportunity to see oneself as an active participant in the future; Opportunity for self-determination –Mastery Engagement in Learning and Opportunity for Mastery

27 Ensuring Validity in Qualitative Analysis Be systematic Use multiple raters Attend to context (e.g. keep track of who said what) Account for outlying and surprising statements Triangulate

28 Resources Building Capacity in Evaluating Outcomes Curriculum and Training (October 2009) on/bceo/index.html