...4 Levels of Measurement Nominal Scale The nominal scale (also called dummy coding) simply places people, events, perceptions, etc. into categories based on some common trait. Some data are naturally suited to the nominal scale such as males vs. females, redheads vs. blondes vs. brunettes, and African American vs. Asian. The nominal scale forms the basis for such analyses as Analysis of Variance (ANOVA) because those analyses require that some category is compared to at least one other category. The nominal scale is the lowest form of measurement because it doesn’t capture information about the focal object other than whether the object belongs or doesn’t belong to a category; either you are a smoker or not a smoker, you attended college or you didn’t, a subject has some experience with computers, an average amount of experience with computers, or extensive experience with computers. No data is captured that can place the measured object on any kind of scale say, for example, on a continuum from one to ten. Coding of nominal scale data can be accomplished using numbers, letters, labels, or any symbol that represents a category into which an object can either belong or not belong. Ordinal Scale The ordinal scale has at least one major advantage over the nominal scale. The ordinal scale contains all of the information captured in the nominal scale but it also ranks data from lowest to highest. Rather than simply categorize data by placing an object either into or not into a...
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...01 What is Statistics? True / False Questions 1. A population is a collection of all individuals, objects, or measurements of interest. True False 2. A sample is a portion or part of the population of interest. True False 3. To infer something about a population, we usually take a sample from the population. True False 4. The techniques used to find out something about a population, such as their average weight, based on a sample are referred to as descriptive statistics. True False 5. There are four levels of measurement-qualitative, quantitative, discrete, and continuous. True False 6. The ordinal level of measurement is considered the "lowest" level of measurement. True False 7. A store asks shoppers for their zip code to identify market areas. Zip codes are an example of ratio data. True False 8. An ordinal level of measurement implies some sort of ranking. True False 9. Data that can only be classified into categories is measured with a nominal scale. True False 10. The terms descriptive statistics and inferential statistics can be used interchangeably. True False 11. A marketing research agency was hired to test a new DVD player. Consumers rated it outstanding, very good, fair or poor. The level of measurement for this experiment is ordinal. True False 12. The Union of Electrical Workers of America with 9,128 members polled...
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...summarizing, and presenting data in an informative way” (2011). Inferential statistics is described by Lind, Marchal, and Wathen as, “The methods used to estimate a property of a population on the basis of a sample” (2011). With the two types of statistics there are also four levels of statistics. These levels are called statistical data measurement. Each level of measurement allows data to be classified. These measurements are: nominal, ordinal, interval, and ratio. Nominal level of measurement as qualitative variables is only allowed to be classified and counted. An example of nominal level of measurement would be gender, because there is no natural order to the outcomes. The next level of measurement is ordinal. This level is used when rating or ranking date. An example of ordinal level of measurement would be how a survey rates a product or service as “Good”, “Better”, or “Best”. Next is the interval level of measurement. This level is similar to the ordinal level; however the different in the values of this level is a constant size. An example of interval level of measurement would be temperature. Finally we have the ratio level of measurement. This level is similar to the interval level, however in this case 0 is meaningful as well as the ratio between two numbers. More so now than ever, statistics plays a...
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...data collection. Data instruments apply “to the levels of measurement of your independent variables and dependent variable” (Lind, Marchal, & Wathen, 2011, p. 5). Survey is a quantitative research approach, not a data instrument. However, “what a scale means and what we can do with it depends on what its numbers represent” (Davis Education, 2015, para. 1). Statistics can be classified into four types or levels, which are nominal, ordinal, interval, and ratio (Lind, Marchal, & Wathen, 2011). Nominal is the easiest of them all. Nevertheless, the ratio is the most complicated of the four type of levels of measurement. Nominal Nominal is hardly measurement. “It refers to quality more than quantity” (Davis Education, 2015, para. 2). A nominal level of measurement is a concerned with differentiating by name. For example, 1 equals male, 2 equals female. Even though, when are using the numbers 1 and 2, they do not symbolize quantity. The two category of 0 and 1 used for the smart cell phone is a nominal level of measurement. They are categories or classifications. “Nominal measurement is like using categorical levels of variables” (Davis Education, 2015, para. 2). Ordinal Ordinal means the order in measurement. “An ordinal scale indicates direction, in addition to providing nominal information” (Davis Education, 2015, para. 3). For example, “Low/Medium/High or Faster/Slower are examples of ordinal levels of measurement” (Davis Education, 2015, para. 3). Interval “Interval...
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...Statistics in the Workplace Statistics are used in my workplace for many reasons. My primary function is to maximize the capabilities of the military treatment facility at the same time ensuring patients receive quality health care in a timely fashion whether it is direct or purchased care. All requests for purchased care are first reviewed for medical necessity and are then re-directed within the military treatment facility for right of first refusal. If the military treatment facility does not have the capability, the requests are forwarded to the managed care service contractor. We also monitor referral patterns, and identify trends relating to network leakage, network care recapture, continuity of care, and customer satisfaction. I work with a team of nurses who don’t work under a clinical directorate. We work under the business directorate. I help to decrease the government’s spending at my facility in particular, on healthcare costs and help to generate revenue in our facility. When purchased care costs are down, our revenue is up. If we see an opportunity to generate revenue in other ways we approach the directorate of business operations to see if we can implement a new plan. Descriptive Statistics According to "Basic Statistical Concepts for Nurses" (2011), “Descriptive statistics are techniques which help the investigator to organize, summarize and describe measures of a sample. Here no predictions or inferences are made regarding population...
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...Workplace The healthcare setting has used research and statistics to aid in standardized care by implementing best practice measures. This is also known as evidence based practice. Statistical information that is gathered is then used to help compare present and past performance, as a guide for planning future development, appraisal of work performed by healthcare staff, hospital or clinic funding, and research (International Federation of Health Information Management Associations, 2012). The purpose of the following paper is to discuss the use of statistics within Mercy Medical Center located in Des Moines, Iowa by using examples and explanations of terms used in statistics such as descriptive and inferential statistics and the four levels of measurement. Within Mercy Medical Center, nursing care is centered around the use of evidence based research thus making it important to understand the basic use of statistics in evaluating research. Hospitals must monitor for the amount of infections which occur in various units continuously since an infection can adversly afffect a patients treatment and may possibly lead to death. One of the infections which can occur is central line acquired blood stream infections (CLABSI). The raw data that is gathered from CLABSI is an example of descriptive statistics. The term descriptive statistics is given to the analysis of data which helps to describe, show, or summarize data in a meaningful way so that patterns may emerge from the data making...
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...are used in every phase in the delivery of health care. This is particularly true as it relates to the cost of providing health care services (Eaton, 2006). At Mercy Medical Center, not unlike any other health care facility, the use of statistics is pervasive throughout the organization. First and foremost Mercy uses statistics to develop and maintain its financial imperatives (Minnis, 2008). Simply stated if actual cost of providing health care services exceeds the revenue generated the organization will have difficulty keeping its doors open. This paper will discuss examples of descriptive and inferential statistics in use at Mercy Medical Center. Also discussed will be how data at nominal, ordinal, interval, and ratio levels of measurement are used within the organization. Finally, the advantages of accurate interpretation of statistical data and improved decision making within the organization will be discussed. Descriptive Statistics An example of a descriptive statistic used at Mercy Medical Center is time spent by the Emergency Department on yellow alert status. Yellow alert is defined by the Maryland Institute for Emergency Medical Services Systems (2012) as ambulance diversion from a designated emergency department that is unable to effectively manage additional patient volume at that time. Several years ago it became an organizational imperative to minimize and indeed eliminate barriers for patients accessing health care services provided by Mercy...
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...survey instrument was created in an attempt to allow the workers to express their views about their individual experiences at BIMS. The survey begins by asking questions about the employee’s feelings toward his or her position and the relationship he or she has with his or her boss. The survey also includes demographic questions that identifies the division they are assigned to and how long they have been employed. As the consulting group one can expect to find that the increase in turnover to be directly related to communication issues between staff and workers, long hours, and low pay. The instrument used for data collection was a survey. A survey is a data collection tool used to gather information on attitudes, opinions, and satisfaction levels of individuals. Types of Data The data included in the BIMS Employee Survey provided by Ballard Integrated...
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...assists in virtually every area for showing areas that need or have improved. Descriptive and Inferential statistics are two types utilized in the workplace and statistics uses four different levels of measurement. The first level of measurement in statistics is nominal this level of measurement this level involves no ranking or order of the data. An example of a nominal measurement in the infusion center would be the different types of blood we administer that day. Whether it is A, B, O, positive or negative neither is placed ahead of the other and it is simply a category of measure. The second level of statistical measure is ordinal level, and it is a ranking system yet does not allow precise differences of measure (Bennett, Briggs, & Triola, 2009). The infusion center frequently conducts patient satisfaction surveys where patients rank how satisfied they are with certain services they receive. This is considered an ordinal level of measure, as there is not a similarity between the categories of satisfaction. Interval level of measure is the third form of measure in the statistical application and has the same interpretation throughout with an arbitrary zero point (Rice University (Lead Developer), University of Houston Clear Lake, and Tufts University,). An example of interval measurement would be patient’s temperatures as each degree of difference would be the same all the way through. In a three patient scenario, one patient had a temperature of 98.6, the next temperature...
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...Types of Measurement Scales Marc Waters MKT/441 June 9, 2014 Cyndie Shadow Types of Measurement Scales Introduction For this week’s assignment, students are to select four types of types of measurement increasing order of sophistication; they are Nominal, Ordinal, Interval, and Ratio. These are categories in which numbers are grouped. This paper will also demonstrate how they can be effective in surveys or questionnaires. Nominal The number we assign to some object, idea, or behavior is entirely arbitrary, although in some cases a tradition may establish the rules of assignment. If measurements are assigned arbitrary numbers, they are called nominal numbers, and their sole purpose in the analysis is to differentiate an item possessing one characteristic from an item possessing a different characteristic. Nominal data is a type of categorical data in which objects do not have a natural, meaningful order. You can count but not order or measure nominal data. Only calculations based on the frequencies of occurrence are valid. Nominal scales have no numeric properties. Qualitative information is obtained from a nominal scale. This means objects are classified by name only. Counting is the only operation that can be performed on a nominal scale. Examples of nominal questions that may be used are: state of residence; gender; or hair color: blonde, brown, red, and black. Ordinal Ordinal data is a type of categorical data in which objects have a natural and...
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...well as the meaning of collected data within the realm of business, and is also commonly used for marketing procedures. Statistics generally deals with the main business elements and the planning process of the data that have been collected through the development of surveys as well as additional tests. Types and Levels of Statistics Even though statistics is general term, there are still two different types of statistics, which includes descriptive statistics that consist of methods for organizing, displaying, and describing data through the use of tables, graphs, and summary measures (Gunning, n.d.). The second type of statistics is inferential statistics, which is a process of describing the population based on the sample results (Gunning, n.d.). Aside from the two main types of statistics that are common, there are also different levels of measurement involved in statistics. There are four levels of measurement, which includes nominal data, ordinal data, interval data, and ratio data. Each level of measurement achieves different results in a survey, and not all researchers will use every level of measurement. Each one of the four levels of measurement serves a different purpose in the study procedure and analysis procedure of statistics. Role of Statistics Statistics serve an important purpose on the decision-making procedure process of a company or companies. This is important to businesses because the statistics analyzed properly will provide an established...
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...team whether you have data from RES/351, and if your team would like to use one team member’s data for the Learning Team assignments in this course. If using data from RES/351: Resources: Data collected from RES/351 Prepare a 700- to 1,050-word written report along with a 5- to 7-slide Microsoft® PowerPoint® presentation for the senior management team or stakeholders of your RES/351 research project to present your findings. Address the following: • Present the chosen situation as an overview—problem, purpose, research questions, and hypotheses. • Describe the instrument used for data collection. • Identify types of data—quantitative, quantitative, or both—and how the data is collected. • Identify the level of measurement for each of the variables involved in the study. • Code the data if you have not done so. Describe how the data is coded and evaluate the procedure used. • Clean the data by eliminating the data input errors made. • Draw conclusions about appropriateness of the data to meet the purpose of the study. If you decide not to use your own data, you can use the Ballard Integrated Managed Services, Inc., case study overview: Resources: University of Phoenix Material: Ballard Integrated Managed Services, Inc., Part 1 Review the Ballard Integrated Managed Services, Inc. (BIMS), Part 1 case study overview. Prepare a 700- to 1,050-word written report along with a 5- to 7-slide Microsoft® PowerPoint® presentation for the...
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...the conditions given, and if the turnover and morale issues have been coming from newer employees or those that are veteran staff. The questions and statements presented are basic to working conditions and include; “You enjoy your assigned shift, You are well trained for your work, How well do you enjoy working for BISM?” (Ballard Integrated Managed Services, Inc., Part 1 Exhibit A) Types of data collected The types of data collected are both quantitative and qualitative data, collected through an employee survey. According to (McClave, Benson, & Sincich, 2011), “quantitative data are measurements that are recorded on a naturally occurring numerical scale.” Most of the survey is questions that require employees to rate their experiences on a scale of one through five, making that data collected quantitative. According to (McClave, Benson, & Sincich, 2011), “qualitative data are measurements that cannot be measured...
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...numerical and graphical methods to look for patterns in a data set, to summarize the information revealed in a data set, and to present the information in a convenient form.” The second type of statistics is the inferential statistics. This type of statistics “utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data (McClave, 2011).” Levels of Statistics Statistics have four different levels. These levels are often referred to as levels of measurement. This first level is known as a nominal level. Within this level, data is sorted into categories without an order. The second level is the ordinal level. This is where the level of measurement decides if any one category is to be ranked higher than another. The third level is known as the interval level. Within this level, “the ranking characteristics of the ordinal level of measurement plus the characteristic that the distance between values is a constant size (Lind, 2011).” The last level is the ratio level. This level has “all of the characteristics of the interval level, plus there is a zero point and the ratio of two values are meaningful (Lind, 2011).” Business Decision Making Statistics play an important role in business because it allows businesses to measure performance and forecast future targets. Businesses use statistics to study facts and...
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...The level of measurement is the relationship among values that are assigned to the attributes for a variable. There are four levels of measurement. Knowing the different levels of measurement helps to decide how to interpret the data from variables as well as deciding the statistical analysis that is appropriate on the values that are assigned. These four levels are nominal, ordinal interval, and ration. The lowest level is nominal and the highest is ratio. The most basic level of measurement is the nominal level. In nominal measurement the numerical values or responses are labels, categories or names. Some examples would be gender, religion, favorite color, etc. The key point about nominal measurement is that it does not imply any ordering among the responses. The responses are merely named uniquely. Ordinal level of measurement is the next level. Data that is noted or recorded at this level is ranked or counted. The data is arranged in some type of order however the difference between the data values cannot be determined or are meaningless. The differences in two ordinal scales cannot be assumed, they are only ranked or rated on a relative scale. Ordinal scales are usually non-numeric thoughts like satisfaction, happiness or discomfort. You can determine central tendency on a set of ordinal data using mode or median. Interval level of measurement is the next level and can be described as measurement based on a scale with a known unit of measurement. In...
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