Economic Testbank

. Provide examples of variable that are at the nominal, ordinal, interval and ratio level of measurement. Explain why.

Analysis of data is important because it allows the researchers to derive meaning from the data collected. Numerous research studies are published online and while the internet is a great resource place to find an article, it is also contain innumerable information that are irrelevant to topic being searched. After scrutiny of the papers selected at the first part of this assignment, two published research studies were selected.

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.

How does one know whether a certain education system is consisted with being reputable and knowledgeable? However, many people have different outlooks on a banking, education system being a failure it all depends on the perspective, engagement, and involvement students put into their learning. A banking, education system can be very influential in all classes that can effectively present students the information to obtain not just to memorize, but also to instead make connections with real world situations like how people interact with one another impacts the way we manage to see each other through communication. What makes a banking system successful is determined on how willing the students will be engaged and adapt in the class, how well

Statistical procedures are important part of any research. Statistics provides us with a tool that, help us to better understand the large and complex amounts of data that, is gathered by other during a research. Statistics are used in many different fields of study from medical research, behavioral research, and political polls, among others. More so, statistics are often used to add credibility to research studies, or to an argument, as well as, in some cases it helps us justify decisions that we make (Hebl, n.d.).

Systematically analyses data and their connections with concepts, to formulate logical and perceptive conclusions and make relevant

The level of measurement for the variable home, would be the nominal level. There are five categories, house, duplex, trailer, apartment, and other. Nominal level data is put into categories with no certain order, and the most typical description of nominal level data is frequencies and percentages (Statistics Solution, 2018). Because the categories in home do not have to be in any certain order, the variable would be nominal.

Assignment Requirements 5002.....................................................................................4 Learning Outcome 1: Be able to identify and select sources of data and information ....................................................................................................................................4 1.1 Discuss the nature of data and information......................................................4 1.2 Evaluate relevant sources of data and

The following are examples of nominal, ordinal, interval and ratio levels variables with explanations of why. Examples of nominal level data would include different medications classifications such as ACE or ARB inhibitors, hypoglycemic agents, neuroleptics, antibiotics, etc. They are considered nominal because they cannot be placed in an order different categories, there is no measureable distance between them and there is no relationship in list order (Marateb, et al., 2014). An example of ordinal level data would include Likert-type scale variables, pain level scales, or social status. They are considered ordinal because they indicate a direction as well as provide nominal information (Marateb, et al., 2014). Interval level data examples

The current exchange rate is €1.00 = $1.50. Compute the correct balances in Bank A 's correspondent account(s) with bank B if a currency trader employed at Bank A buys €100,000 from a currency trader at bank B for $150,000 using its correspondent relationship with Bank B.

Data Analysis is defined as "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data. (Statistician John Tukey, 1961)” In general, Data Analysis is used to check the validation of the vaguely collected data in terms of variations and profitability. However, if Data Analysis is not used we cannot obtain the accurate, factual and optimum solution of the given challenge. Data Analysis tools helps us to understand the question and produces answer in a detailed space. It also helps to find the gaps between data such

According to class discussion, the way researchers decide whether to use qualitative or quantitative analyses in their research design depends on the research question. Often, the question naturally lends itself to either qualitative or quantitative analysis (Dalton Lecture: Nov. 9). The same is true when deciding which method to use for evaluation research. Quantitative methods of analyses are often used to identify the specific effects of a social program. However, when investigating a program’s process or seeking to better understand the complexities of a social program, qualitative analysis is the common choice (Dalton Lecture: Nov.16). When conducting quantitative research, researchers must be aware of levels of measurement because the way in which concepts and variables are measured influence the validity of the results (Pg. 65). There are four levels of measurement that researchers must be aware of when working with quantitative data: nominal, ordinal, interval, and ratio (Pg. 76). Levels of measurement are chosen as researchers operationalize their variables. Understanding which level of measurement is appropriate for each variable helps one decide which measure of central tendency to report (Pg. 79). For example, if the variable is happiness and participants are asked to rank their level of happiness on a scale of 1 to 10, this type of measurement is ordinal. Therefore, the best measure of central tendency to report is the median,

A point that requires attention is that all the information derived from the measurement system should be accessible to all the different groups affected. Transparency and openness between the different departments as well as

b. In this case to get the correlational coefficient of the variable if it is ordinal, then I could use Spearman rank rho coefficient and if it is interval or ratio level I could use the Pearson product coefficient of correlation. In the end I can check if the correlation is statistically significant by using the t test for significant correlation coefficient.

An Ordinal scale is a measurement which looks at the variables where order matters but the difference does not matter. While thinking of the ordinal you must think about the word order. Hence, it is easy to remember as in this scale only order