Week+3+Notes

Week 3 – July 16, 2011
Part 1 Use of Theory Testing Hypotheses Reviewing the Literature Sampling Comparison Overview of Descriptive & Inferential Statistics

Part 2 Data Collection & Analysis emphasis on Quantitative Research Descriptive Statistics Scales of Measurement

**NOTES ON READINGS**
>
 * Text: P: 15, 27, 29-41, 43-57
 * Text: 107-110; 115-120


 * **Sundar, S. S., Knobloch-Westerwick, S, & Hastall, M. R. (2007). News cues: Information scent and cognitive heuristics. //Journal of the American Society for Information Science and Technology//, 58(3), 366-378.**


 * **Lingering Question:** Sundar, et al. mentions administering a pre-test to a limited number of German and American respondents that rated various news sources from “not at all credible” to “highly credible” in order to choose 6 highly credible and 6 low credible media sources for the study (372). Did these same respondents also undergo the main experiment or were they excluded from the main experiment since having taken the pre-test could alter responses to the main experiment? What, if anything, did the researches do with the demographic information taken from participants (did I miss this in the article?)
 * **Point of Interest:** By utilizing a familiar format such as a mock-up of Google News (on in the case of this study, World Wide News), participants can navigate the study in a self-guided manner. I wonder whether any of the participants had never experienced Google News prior to the study and whether the newness of the format might have affected the results to some degree. By drawing responses from a large sample size of over 523 individuals (with the start of the chain of participation being university students who then forwarded the link to the study onto friends and families), this surely occurred, however, it does not appear that the study asked participants whether they have used news-bot services in the past.


 * **Japzon, A. & Gong, H. (2005). A neighborhood analysis of public library use in New York City. //Library Quarterly//, 75(4), 446-463.**

//__Reference__// Odeh, O.O., Featherstone, A.M., & Bergtold, J.S. (2010). Reliability of statistical software. //American Journal of Agricultural Economics//, 92(5),1472-1489. Retrieved from __[]__
 * **Lingering Question:** Are there any library systems that do choose to shift funding to disadvantaged neighborhoods/library branches? What might prevent libraries from doing so? Why do users of disadvantaged library neighborhoods tend to use materials in-house rather than check them out?
 * **Point of Interest:** Since this article mentioned that the regression analysis was achieved by using the program SPSS, I began to wonder what other software programs there are available, and the reasons for using one over another. I then located the Odeh, et al. article referenced below which I have skimmed and have bookmarked to read more closely later. Interestingly, Odeh, et al. concludes in pertinent part as follows: " The findings underscore the need to cross-validate research results. Applying different software packages to the same estimation problem should occur to develop confidence in a solution... Teachers of econometrics need to make students more aware of the limitations of the software packages available... In addition, implementing multiple packages and accepting a solution when the results agree across packages may be a more reliable approach than relying on a single package." (p. 1487)

> > //__References__// > **Pezzullo, J.C. (2011). Interactive Statistical Demonstrations and Tutorials. Retrieved from [] ** > > Wang, P.-Y., Vaughn, B.K., & Liu, M. (2011, 28 April). The impact of animation interactivity on novices' learning of introductory statistics. //Computers and Education//, 56(1), 300-311. Retrieved from [] >
 * **Byrne, G. (2007). A statistical primer: Understanding descriptive and inferential statistics. //Evidence Based Library and Information Practice//, 2(1), 32-47.**
 * **GREAT SUMMARY OF TERMINOLOGY, ETC.**
 * **Lingering Question:** Will I ever feel comfortable about my level of understanding of the basics of statistics?
 * **Point of Interest:** Gillian's article caused me to wonder about the ways in which statistics can be learned by students in the age of the internet. I recall learning some of the terminology and concepts in this article at some point in high school (likely in Algebra II), but for all practical purposes I am learning this for the first time as an adult. As a visual and experiential learner when it comes to more abstract concepts, the graphics in Gillian's article helped me to better understand the ideas she presented. I located an interesting article suggesting that using interactive animated tools can increase understanding and lower level application of statistical concepts (Wang). Along this line, I located J.C. Pezzullo's annotated bibliography of “Interactive Statistical Demonstrations and Tutorials,” which I have bookmarked for future reference.
 * **Point of Interest:** Gillian's article caused me to wonder about the ways in which statistics can be learned by students in the age of the internet. I recall learning some of the terminology and concepts in this article at some point in high school (likely in Algebra II), but for all practical purposes I am learning this for the first time as an adult. As a visual and experiential learner when it comes to more abstract concepts, the graphics in Gillian's article helped me to better understand the ideas she presented. I located an interesting article suggesting that using interactive animated tools can increase understanding and lower level application of statistical concepts (Wang). Along this line, I located J.C. Pezzullo's annotated bibliography of “Interactive Statistical Demonstrations and Tutorials,” which I have bookmarked for future reference.

> > > //__Reference__// > Shachaf, P., Oltmann, S.M., & Horowitz, S.M. (2008). Service equality in virtual reference. //Journal of the American Society for Information Science and Technology//, 59(4), 535-550. Retrieved from E-prints for Library and Information Science (E-LIS): [] >
 * Carter, D. & Janes, J. (2000). Unobtrusive data analysis of digital reference questions and service at the Internet Public Library: An exploratory study. //Library Trends//, 49(2), 251-265.
 * <span style="font-family: Arial,sans-serif;">**Lingering Questions:** How long did it take to examine the data? If one of the reasons for rejection is that the IPL reached its daily quota of questions, how were the daily collection of questions answered (strictly chronologically? pick-and-choose until the quota is met?) I'm curious about the questions that were potentially passed up and then categorized as rejected due to quotas and whether these questions had any commonalities or if certain groups of users were discriminated against due to the nature of their questions or for other reasons. Interestingly, the 2008 Shafhaf, et al. article referenced below (which I located by using Google Scholar to find articles that cited the Carter, et al. article) concludes as follows: " <span style="font-family: Arial,sans-serif; font-size: medium; line-height: 24px;">Do virtual reference librarians provide equal quality of service to diverse user groups? Based on our findings we can tentatively answer “yes,” since no significant differences based on race or gender were found in the quality of e-services that libraries provide to the public. The quality of service to all user groups was equal in terms of courtesy, reliability, and timely response. We conclude that the virtual environment has the potential to enable unbiased services to all users."
 * Point of Interest:** <span style="font-family: Arial,sans-serif;">Carter, et al. reveal that the IPL began its digital reference system in 1995, and this data was derived from January-March 1999 for this article that was published in 2000. While quite interesting in its own right, I wonder how the results for this time period would have compared to the years prior. On the other hand, given the sheer volume of questions to examine (3000 questions of the total of more than 40,000 questions posed from the beginning of IPL's digital reference service) and the innovative statistical nature of this study (versus past studies that were more anecdotal in nature or which focused on the nature/existence of this type of services), and the inferred time and expense it took to administer this study, the reader does get a good sense of the rationale behind limiting the study to the first quarter of 1999.

> study, you should also plan your data analysis, "proceed[ing) logically from purpose to > measurement to analysis to conclusions" (Spirer et a!., 1998, p. 13). One of the first steps > in your data analysis is to summarize your results; this is the role of descriptive statistics. > In this chapter, we will focus on describing the results related to a single variable; for > example, you may want to know how much Internet experience the college students in > your sample have. " > > Chapter 37: Compar ing Means: t Tests and Analysis of Variance: "Often in your research, you will want to compare different groups of people in terms > of the mean (average) values of particular variables. For example, suppose you are > testing a new online catalog interface and want to determine whether users prefer it to > the existing interface. After giving a questiOIU1aire to people who have used one or the > other interface, you want to compare the responses of the two groups. Two statistical > t e chnique s - the t test and analysis of variance (ANOVA) -he lp you make these types > of comparisons. " >
 * **Wildermuth, B. M., ed. (2009). Applications of Social Research Methods to Questions in Information and Library Science. Chapters 33 & 37. Pages, 338-347 & 383-392. [Oncourse]**
 * __**Notes**__
 * Chapter 33: Descriptive Statistics: "When you first develop your research question and plan the way you will carry out your

Due:
 * **Analysis A (Literature Review) --- Per Week 1's Class Notes:** **For Article Analysis A: Literature Review, use Web of Science __and__ Google Scholar** **for this part: "Look up the cited article in Social Sciences Citation Index. Examine the citations for all of the articles which cite it. What types of articles are they? Who seems to find this article useful? If none cite it, speculate on why this might be."**