Create a 450-600 words, in current APA format, should use at least 2 scholarly articles as references, and one biblical scripture for each response.
As part of its bankruptcy restructuring, General Motors (GM) launched an ad campaign that revealed glimmers of a streamlined GM: fewer brands (Cadillac, Buick, Chevrolet, GMC, and fewer models within each brand.
1. What research would you have done to determine which vehicle models GM should retain or drop?
2. What would you have measured and with what type of measurement scale?
12.7 Businesses frequently use surveys to measure quality. In an effort to evaluate the perception of customers and identify product quality, surveys are used as a mechanism to gather information. Data analyses using insignificant, interval and ratio data are generally straightforward and transparent.
In the scenario, a Likert scale is used to collect various survey ratings using a ranking quality from high to low or best using five levels of classification in the consideration of strongly agree to strongly disagree. Likert scales are considered to be one of the most popular methods of measuring attitudes in summated ratings. The individual responses strongly agree through strongly disagree are assigned numbers, usually ranking from 1-5. In this manner, the responses to the various items are quantified and may be summed across statements to give a total score for the individual on the scale.
If Strongly Agree (SA) represents the most positive attitude, how would you value the items below? Record your answers to the items.
The program is not very challenging. SA A N D SD
The general level of teaching is good. SA A N D SD
I really think I'm learning a lot from this program SA A N D SD
Students' suggestions are given little attention SA A N D SD
The program does a good job of preparing one for a career SA A N D SD
The program is below my expectations SA A N D SD
In what two different ways could such responses be used? What would be the purpose of each?
A fundamental reason for analyzing ordinal data as interval data might be the argument Likert-type data has unique data analysis procedures. Numbers associated with the categories serve only as labels. Numbers assigned to groups express a greater than relationship; however, how much greater is not implied. The numbers only indicate the order. Examples of ordinal scale measures include letter grades, rankings, and achievement (low, medium, high) (Maurer & Pierce, 1998). A Likert scale consists of a series of four or more Likert-type items that are combined into a single composite score or variable during the data analysis process. One method the responses can be used is combined, the items are used to provide a quantitative measure of a category or criteria in the research study. According to Linacre 2002 typically the researcher is only interested in the composite score that represents the character or personality trait.
The difficulty of measuring attitudes, character, and personality traits lies in the procedure for transferring these qualities into a quantitative measure for data analysis purposes. Attitude reflects a person's character and will. Christians are encouraged to be Christ like and to keep him on the forefront and to seek God in all things and reflect a positive attitude "So that you may not be sluggish, but imitators of those who through faith and patience inherit the promises (Hebrews 6:12)."
Rating scales have several uses, design features, and requirements. Likert scales can be used as a means of course evaluation to provide feedback on the content and facilitation of coursework. Likert-type items as single questions that use some aspect of the original Likert response alternatives, while multiple questions may be used in a research instrument. Likert scale data are analyzed at the interval measurement scale.
According to Allen and Seaman 2007 it would take twelve separate responses to discover a person's attitude toward a textbook and an instructor with the semantic differential. With Likert scaling, two responses would yield the same data. This efficiency can best be appreciated by the overloaded instructor. Students can evaluate numerous facets of instruction, course content, and the instructor in a relatively short period of time.