Pu 410 Unit 2 Assignment

b. Ordinal: This is a measurement that represent the order of a particular stat. A good example of this would the placement in a contest, 1st, 2nd, and 3rd.

Above is an example or both primary and secondary data which is all quantitative being based on proven facts and subject to continual improvement.

Typically there are four different levels of measurements for variables. These are nominal, ordinal, interval and ratio. Nominal measurement is a numerical value. An example in the High School Longitudinal Study database used are the year’s math teacher has taught high school math. Ordinal measurement are the features that can be categorized. An example of this would be if you’re ranked the highest education of the parents. An ranking example is reflected below chart

Second, questions one through ten qualify as ordinal data because of the relative rankings without consistent distances. Finally, the time worked for BIMS qualifies as ratio level data because it is easily ordered, consistent differences and zero is meaningful (McClave, Benson, & Sincich, 2011).    Each level of data has unique characteristics, which dictate the way the information is calculated, summarized, and presented.

i.e. This is often used in surveys or questionnaires when participants are asked to rank items or categories by preference, importance, or another dimension.

Interval level data builds on the ordinal level data because the data may become also ranked equal intervals between categories (Walker & Maddan, 2009, p. 34-35). Interval level data has values of equal intervals that mean something. For example, a scale might have intervals of ten degrees. Other examples of interval level data are Celsius Temperature or Fahrenheit Temperature, IQ (intelligence scale), ASVAB scores. Time on the clock with the minute and hour hand.

Nominal data does not have an inherent order. Dichotomous data is a type of nominal data which have one or two levels only. Ordinal data is made up of variables categories with undefined intervals based on an inherent order. Interval data can be continuous or discrete and is made up of an inherent order with equal intervals. For continuous data, any value in a continuum is used irrespective of the manner of reporting. Discrete data uses specific values which are expressed as counts (Fletcher et al., 2012).

For each of the four items listed. Indicate whether the variable is categorical or numerical. If it is numerical. Is it discrete or continuous?

"Descriptive statistics is the summary of important aspects of a data set" (Jaggia & Kelly, 2014). To use descriptive statistics, I would use frequency distribution. "Frequency distribution of qualitative data groups the data into categories then records the number of observations that fall into each category" (Jaggia & Kelly, 2014). If I use ordinal data, it will allow us to categorize and rank the data. The data will then enable us to determine if recognition will help the high turnover rate at UnitedHealth Group.

Nominal level measurement is considered the weakest level of measurement. This method measures variables described by names or labels. Words, letters, numbers, or symbols can be used. These values just name the attribute. A scale is used to group categories in order. An individual’s level of pain can be determined using the scale:

This would be quantitative, because it is showing the actual dollar amount and is not grouping it into different categories.

This variable is nominal because the choices do not have a ranking order. My independent variable is feelings about the Bible which also came from the GSS dataset. Feelings about the Bible is measured by, Word of God, Inspired Word, Book of Fables or Other. The participants were asked, “Which of these statements comes closest to describing your feelings about the Bible” and they could pick from one of three choices which were, “The bible is the actual word of God and is to be taken literally word for word (1), The bible is the inspired word of God but not everything in it should be taken literally (2), word for word and The bible is an ancient book of fables, legends, history and moral precepts recorded by men (3).” Feelings about the Bible is an ordinal variable because there is a ranking order, but the distance between each is not known. I used Correlations to test my hypotheses and these tests were done using SPSS 2008.

Quantitative Research mainly focuses on gathering mathematical statistics to explain a phenomenon. According to Locke, Silverman & Sprirduso (2010), there are five statistics that are used by researchers: descriptive, correlation, and quasi-experimental/experimental, single subject and meta-analysis. Each subcategories technique is used in Quantitative to describe something about the study. The intention of descriptive is to explain a sample on a specific variable. Subsamples can also be defined on the same variable (Locke, et. at 2010). Some of the frequently descriptive research formats consists of the following: Survey research, political polling, and Delphi surveys. The purpose of correlation is to anticipate a standard variable, or to examine a model of the interrelationship between variables consumed to predict a variable (Locke, et. at p.95). Formats used are: predictive, multiple regression, casual modeling, structured equation modeling and path

Ranked data can also be represented using the same methods as for nominal data, but the order is important.

Sometimes in statistical analysis, non-numeric variables are given numeric values. For example, students who eat healthy breakfast are +1, the students who eat an unhealthy breakfast are 0 and the students who do not eat breakfast are -1. This is the way to get who is in which group but don 't really have value.