Making Research Decisions Essay

Custom Student Mr. Teacher ENG 1001-04 24 October 2016

Making Research Decisions

Chapter 12 – Discussion Questions (Making Research Decisions) # 5 a Yes—Depends—No: One problem would be that “depends” is very vague and doesn’t give reasons as to why someone would pick “no” at some point and “yes” at another. A way to make this better would be to add a “please describe” line or change the wording all together. There is no way to express “don’t know” or “undecided”. b Excellent—Good—Fair—Poor: One problem with this would be that it may not have as valid a measure as say an 8 point scale, “as the number of scale points increases, the reliability of the measure increases.

Second, in some studies, scales with 11 points may produce more valid results than 3-, 5-, or 7-point scales” (Cooper and Schindler, 2011). What may be “good” to someone may be “fair” to another. c Excellent—Good—Average—Fair—Poor: People may have trouble telling the difference between “good” and “average” because shouldn’t “average” already be “good”? d Strongly Approve—Approve—Uncertain—Disapprove— Strongly Disapprove: An issue with this would be that it is an unbalanced scale, “unequal number of favorable and unfavorable response choices” (Cooper and Schindler, 2011). Chapter 5 – Discussion Questions (Terms in Review) # 1- 3

1. a Purpose: This is one way that managers can study and chose information. This way evaluates the “explicit or hidden agenda of the information source” (Cooper and Schindler, 2011). b Scope: The scope applies to the content of the information and the extent to which it covers such as any kind of limitations or time period sensitive data. c Authority: This factor looks at the quality and level of the information, for example what the source credentials are and whether it is primary, secondary or tertiary. d Audience: This has to do with the type, any specific characteristics, of people or groups of people “for whom the source was created” (Cooper and Schindler, 2011). e Format: This has to do with the way the data is presented “and the degree of ease of locating specific information within the source” (Cooper and Schindler, 2011). 2. Define the distinctions between primary, secondary, and tertiary sources in a secondary search.

A primary source is one that uses a valid original work such as raw data and is the most valid type of data. Secondary sources interpret the data and research from a primary source, an example of this would be a textbook or news article. A tertiary source is one that presents and interprets data that has been found from secondary sources. 3. What problems of secondary data quality must researchers face? How can they deal with them?

One of the biggest problems with secondary data is the fact that the information being citied is an interpretation of the original data. The best way to avoid a misinterpretation of the data is to look for the original or primary source that is referenced in the secondary source and directly quote or use the data from that. This will eliminate the chance of having misinterpreted data put into an important project and it will lend you an additional source. Researchers should evaluate and select information sources based on the 5 factors. Read the case study, State Farm: Dangerous Intersections. Answer discussion questions 1 through 5. 1. Identify the various constructs and concepts involved in the study.

To answer this question we must define what a concept and construct is, “an image or idea specifically invented for a given research and/or theory-building purpose” (Cooper and Schindler, 2011). A concept is “a bundle of meanings or characteristics associated with certain events, objects, conditions, situations, or behaviors” (Cooper and Schindler, 2011). A construct of this study is that if State Farm gives money to the states of dangerous intersections to fix them this will decrease the amount of claims in that area due to the intersection becoming safer due to alternate construct. A concept would be that State Farm cares about their customers. Another construct would be that the amount of claims in a given intersection is due to poor construct. Another concept would be that State Farm wants to help states to improve their intersections. 2. What hypothesis might drive the research of one of the cities on the top 10 
dangerous intersection list?

An example of a hypothesis that may influence the research of one of the top 10 dangerous intersection list would be “This intersection is one of the top ten most dangerous intersections in the United States” or “This intersection is where 50% of the states accident claims occur.” 3. Evaluate the methodology for State Farm’s research.

I would say that State Farm’s methodology is concrete because it specifies exactly what the variables are and how the study is constructed. They also implemented a measurement system for classifying accidents. 4. If you were State Farm, how would you address the concerns of transportation engineers?

I would provide suggestions of what the constructs of the safest intersections in a comparable size city are and help the engineers come up with a solid and safe plan to reconstruct the intersection. I would need to make sure the engineers understood the idea of future studies as well as how the grant could assist them. 5. If you were State Farm, would you use traffic volume counts as part of the 
2003 study? What concerns, other than those expressed by Nepomuceno, do you have?

My concerns would be out of date data. That data would be almost ten years old and may not be the most accurate at this point. I would want to complete more relevant data for say the last 5 years. I would think it as prudent to include traffic volume counts and compare them to different areas because if there is less traffic at a given site there is more then likely going to be fewer accidents. I would propose to use different studies that compare different volume counts in different geographic areas to make the statistics more complete.

Free Making Research Decisions Essay Sample


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  • University/College: University of California

  • Type of paper: Thesis/Dissertation Chapter

  • Date: 24 October 2016

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