Blue-footed Boobies from the Galapagos


More info:


Science Fun

Brian's Class Materials- SPRING 2012 - SEYS 778

SEYS 778 Home

Spring 2012

 SEYS 778 – Seminar Research in Science Education II

Wednesday 4:30 to 7pm

Powdermaker Hall Room 004

Data Collection (II) – Analysis and Figures, Tables

Much thought must be put into selecting the best way to analyze the data you collect, because it is through a well structured analysis that outcomes become clear and most importantly, defensible. Therefore,  analyzing and summarizing the data must show the outcomes are dependable, accurate, reliable, correct.  It is an attempt by the researcher to find meaning, to answer the question, “So what?”

A. First attempts to analyze data:

1. Look for patterns, try to identify themes (eg. Any data that accumulates and is repetitive,  key trends,  common phrases used in free-response statements).

2.  Define a system for coding information/data if not established earlier in the study. For example, using a Likert scale in a questionnaire already establishes set ways to analyze and report data.   Interval data such as test scores are often used to document outcomes.  

3.  Try concept mapping to help you visualize the relationships that emerge, particularly in action research-type studies.

4.  Consider whether your analysis should employ statistics.  Descriptive statistics measure central tendency – the mean (the average), median (middle score), mode (most frequently occurring score(s). Variability indicates how spread out a group of scores are – Standard deviation is a measure of distance from the mean that helps define how much a particular score deviates from the average. Relative standing- Percentile ranking,  Correlation between 2 or more factors?

5.  Inferential statistics are used to determine how closely samples match the population at large.  Statistical analysis is run on data to find relationships that are deemed “significant.” These include tests of significance of correlation, difference between means, analysis of variance and chi- square for non-parametric statistics.

B. Presentation of results:

1.   Consider what format would best illustrate the results of the data analysis.  What presents the clearest picture … grids, graphs, pictures, diagrams, charts, tables of figures?              

2.   All illustrations are titled in a final report.  Most are embedded in the body of the paper or put in the appendix.   See examples from text.

C. Reflecting on the results of A. above to reach conclusions and implications.

1.  An important aspect of analysis is finding implications of the data when the analysis is complete.  What do the findings suggest?  What questions remain open to further investigation?   Avoid unwarranted assertions based on sloppy analysis of thin data.

2.  Consider the role of theories related to your area of research to help interpret data outcomes.

ACTIVITY GOALS:  Find a group in which you can discuss mutual concerns.

Working groups:

A.   Instructional innovations and student attitudes/achievement

B.  Innovative” programs – Case studies and descriptive reports

C.  Other

The goals for this activity are to help you resolve study issues that pertain to the following questions:

1. How will I tabulate the data I collect?

In a prior activity, tabulation was discussed.  Tabulation of data requires you to define how you will organize and categorize the data you collect.

2. How will I analyze the data once it is tabulated? 

    Does the data need to be summarized using descriptive statistical measures, such as averages, or means?   What other questions are being looked at?  

3.  How will I report the outcome(s) of my study?