Data Analysis Techniques

Powell and Connaway:

Statistical Analysis - Concerned with the development and application of methods and techniques for organizing and analyzing data so that the reliability of conclusions based on the data may be evaluated objectively in terms of probability. (Powell pg.261) There are two different types of statistical analysis: theoretical which deals with mathematical aspects of statistics, and applied statistics deals with practical applications of statistics.

Steps involved in statistical analysis (Powell pg. 263-264):

1. Establishing of categories

- The set of categories for any one variable should be derived from a single classifactory principle, which is determined by the research question or hypothesis being investigated.

- Each set of categories should be exhaustive.

- The categories within each set should be mutually exclusive.

- The development of categories should be based on a sound knowledge of the subject matter and an anticipation of likely responses.

2. Coding the data

- Once a category has been established and data assigned to them, it is necessary to convert the new data or responses to numerical code, so that they can be tallied.

- Coding needs to be reliable and consistent.

3. Analyzing the data

- Decide whether to use descriptive statistics, inferential statistics or both.

4. Cautions in testing the hypothesis

- Statistical inferences are based on probability, and one can never rely on statistical evidence alone for a judgment of whether a hypothesis is true. It is also important to remember that a single statistical acceptance of a hypothesis does not prove it to be true with absolute certainty.

Wildemuth:

Content Analysis - the systematic, objective, quantitative, analysis of message characteristics. (Neundorf 2002) The "message" refers to information that travels from source to destination. Content analysis was originally developed to analyze texts such as journal articles, newspapers, books, responses to questionnaires, and transcribed interviews (Wildemuth pg.297).

Identifying the units for analysis - There are two basic types of units of content to define after you have chosen a research question: sampling units and recording units (Riffe 2005). Recording units are the elements of content that are coded (Wildemuth pg. 299). The types of recording units are: physical, conceptual, and temporal. Sampling units are usually collected from the overall population of the text or other media of interest.

Qualitative analysis - A research method for the subjective interpretation of the content of text data through the systematic classification process of coding and identifying themes or patterns (Hsieh & Shannon 2005). Qualitative content analysis goes beyond merely counting words or extracting objective content from texts to examine meanings, themes, and patterns that may be manifest or latent in a particular text (Wildemuth and Zhang pg. 308).

Discourse analysis - The analysis of discourse. Tends to focus on either the particular types of conversations (the reference interview) or formal texts (professional literature). Such units of information comprise social texts (expressions of our society) and function to support interpersonal relationships, institutions and ideologies within that society (Wildemuth and Perryman pg. 320).

Analytic induction - A specific form of inductive reasoning used to analyze qualitative data. It is a formalized method for developing and refining a theory or hypothesis, directly from the data (Wildemuth and Spurgin pg. 329). The hypothesis and definitions must apply to all cases of your sample.

Variable - A property of an object, person, or event that can take on different values (Howell 2004). They can also be defined and operationalized at different levels of measurement. Nominal variables are those whose possible values are categories, with no true numerical value that can be assigned to them (Wildemuth pg. 339). Ordinal variables are those for which the values can be rank ordered (Bernard 2000). Ratio-level variables are ordered and have values at equal intervals, they have a true zero point (Bernard 2000).

Article Review #2

Schlipp, J. (2010). Creative thinking: A student-centered approach to plagiarism and copyright. Kentucky Libraries, 74(3).

Introduction:

The scope of this article is to help teachers and librarians help promote the correct way to cite and give credit to the person who created the work. The most important aspect of this article is determining the difference between plagiarism and copyright infringement. The University of Northern Kentucky library has put together several films and a website dedicated to creative writing of original material and facts about plagiarism and copyright. This article definitely helped me focus on a more narrow scope and what I want to do with plagiarism. I want to develop some sort of lesson plan or material to promote the awareness of plagiarism.

Problem Statement:

According to a Microsoft survey in 2008, more than 50% of today’s teens aren’t familiar with the consequences of copyright laws and illegal downloading (Schlipp 2010). Schlipp intends to raise awareness and give teachers and librarians creative ways to teach this.

Literature Review:

This work draws from a couple of studies from Microsoft and studies collected by the University of Northern Kentucky. This article itself doesn’t extend the research but material held within it can definitely spawn new research. There are several tools at hand and using these and holding another study/survey hopefully can yield some positive results. If they don’t you can see if these lessons and teachings are effective and build from there.

Method:

All research was done digitally through online surveys. The population was strictly teenagers and high school students.

Caveat:

Testing the validity of plagiarism studies is extremely difficult. Who knows if the students are being truthful. It’s very hard to make a factual statement when it’s such a sensitive subject. Students don’t want to say they’re cheating so some bias may occur. Hopefully these lessons and activities well help spread the word on plagiarism and copyright infringement.

Data Collection Techniques

Powell and Connaway:

Sources of error: Error with questionnaires occur frequently, but they are not limited to just questionnaires.

-Researcher bias: When the researcher develops the questionnaire so they receive the desired results.

-Sponsorship bias: When a researchers caters to the sponsors and skews the results.

-Imperfection of design: Weaknesses in the design of the questionnaire can result in innaccurate results.

-Respondent interpretations: Interpretation of "facts" may be skewed.

-Time lapse: Answers to questions tend to vary over time.

-Circumstances: Mood and careless answers can skew results.

-Response bias: Number of respondents may be too low and skew results.

-Reactive insight: Questionnaires can bring up sensitive topics which cause the survey taker to create a bias based on their reaction.

Final editing - There are a couple of suggestions that will make your final survey desirable and easy to take. Making the survey as short as possible will encourage accurate and well thought out answers. Always ask questions that the researcher doesn't already know. Unnecessary and redundant questions should be avoided.

Wildemuth:

Data Collection - Should be a relatively straightforward activity in the case of server-side transaction log studies. Researchers should monitor data logging and ensure that data are being captured as expected. (Wildemuth pg.170)

Transaction Log Analysis - The captured data represent a record of events as they actually occurred, without re-framing and recall errors prevalent in many other data collection methods. The quality of your data will not be dependent on the study participant's memory of the interaction or on his or her ability to describe the interaction. (Wildemuth pg.167)

Think-aloud Protocol - A research method used to understand the subjects' cognitive processes based on their verbal reports of their thoughts during experiments. You request subjects to speak aloud, reporting what they are thinking while they are performing tasks during an experiment. (Wildemuth pg. 178).

Types of think-aloud protocol:

-Concurrent protocols - they allow the subject to first complete tasks without saying anything

-Retrospective protocols - allows the subjects to complete the tasks in a more natural way