The Different Quantitative Inquiry Designs and What Influences The Alternative of Their Use

According to Vaus (2001), the function of a research pattern is to ensure that the evidence obtained enables a researchworker to answer the initial question as unambiguously as possible. It gives commission and systematizes the research. The method you choose will affect your solvent and how you conclude the findings (Kothari, 2014). Most scientist are interested in getting reliable observations that can help the understanding of a phenomenon. Selecting the correct type from the different research method can be a little daunting, at first (Kothari, 2014). According to Kumar (1996), there are so many gene to take into invoice and evaluate. This is before looking at the statistics required and perusal the preferred method acting for the individual scientific discipline. For different disciplines, there can be a huge change of research method acting to choose from, and a researcher will have to justify their option. Whilst slightly arbitrary, the best way to look at the various methods is in terms of durability (Kumar, 1996).

According to Kothari (2014), there are two main attack to a enquiry problem: quantitative and qualitative enquiry approaches. In a nutshell, quantitativeenquiry generates numerical information or information that can be converted into numbers. It centering more in tally and classifying features and constructing statistical role model and figures to explain what is observed (Kothari, 2014). According to Creswell (2013), quantitative research aims to numerically describe a phenomenon of interest (descriptive research), explore relationships among variables (correlational research), or manipulate variables in order to measure the effects (experimental research). Qualitative Research on the other hand generates non-numerical data. It focuses on gathering of mainly verbal data rather than mensuration. Gathered information is then analyzed in an interpretative manner, subjective, impressionistic or even diagnostic (Wikipedia Encyclopedia, 2005).

Quantitative inquiry requires the inquiry to skeletal system a research question based on certain important research conception s (Bryman, twenty 16). First is the unit of analysis which refers to the object or result that you are enumeration or measure , that is, the cases that make up your sample. These might be individual mass (as in a survey), interaction (as in an reflexion ), or menold age (as in a census). Second is a variable which is a concept that describes a phenomenon in a way that can be counted or measured (for example age, sexuality, IQ, mathematical power, involvement in sportsman ). Variable can be self-employed person, that is, influences, acts upon, or causes change in another variable; or dependent, that is, is acted upon or is the effect of the prior variable. The third important concept in choosing quantitative research questions is attributes which refers to the category into which you divide your variable . For example, gender might be “male” and “female”; age might be “below 20 ”, “between 20 and XL ”, and “over 40 ”; and mathematical ability might use the scores from a psychometric test (Bryman, 2016). According to Creswell (2013), a quantitative research question payoff a subject of interest and restates it in operational terms, that is, in terms of how you will gather the empirical data that will allow you to test your guess in order to categorize or describe the relationship s between your variable quantity. Quantitative research requires you to restate your research question as a hypothesis. This is your best guess about the relationship between the variable that you will then set out to test (Creswell, 2013).

Quantitative Research Designs

Descriptive Research

Descriptive studies are designed to amplification more information about characteristics of a topic of interest (Kothari, 2014). In descriptive inquiry , measurable or observable data are collected to garden truck a categorization or description of the variables or combinations of the variables. These can result in statements such as, “XX percent of lady friend between the eld of tenner and 15 read for pleasure for more than five 4 senses of hour per workweek .” Descriptive level inquiry is most appropriate when very little research is available on the topic. Component need to be described before they can be tested (Kothari, 2014). According to Fraser Wellness Say-so (2011), descriptive level research includes sight research or case bailiwick methodology. Survey research involves gather data, usually through a written survey/questionnaire . Surveys can either be cross sectional, which involves the accumulation of data from selected individuals in a single time period and/or longitudinal, which involves data solicitation at two or more times in order to describe changes over time (Fraser Health Agency , 2011). The determination of survey research is to describe characteristics, opinions, posture, or behavior as they currently exist in a target population. A case study design explores in astuteness a single player, chemical group, incident, or residential district through detailed information time (Fraser Health Say-so , 2011).

One advantage to descriptive stage research is that the investigator is able to collect a large amount of data. However, even though there is largeness of data, it tends to lack profundity for the sample. On the other hand, case written report research provides deepness and richness of data but lack breadth since it is limited to one person or upshot. One important distinction of descriptive story research is that nothing is manipulated or controlled. Phenomena are studied in real-life situations. Thus, cause and issue relationships cannot be determined using this design. Information are analyzed using descriptive statistics such as absolute frequency, means, and percentage. A comparative descriptive design hyperkinetic syndrome to the basic descriptive design by making it possible to compare two or more groups on the broker of interest (Kothari, 2014).

An example of this design is McAuliffe’s (2007) written report on oral examination hygiene. The purpose of this survey was to explore and identify factors that may influence nursing students’ oral hygiene practice in hospitalized patient. Broker -isolating inquiry s ask the question “What is this?” which is what McAuliffe is doing here. Only an object and object lens, not hypotheses, were used in this study. A survey was used to gathering the student’s perspective on what they were Edward Thatch versus what they practiced as it relates to oral hygiene practices. Descriptive statistic (percentages) were performed to solution their objectives. Findings indicated that there was incongruence between what the students thought they were taught and what was actually taught in the schoolroom. Further, students were picking up not-necessarily good habits from their nanny role modelling within the clinical Seth (McAuliffe, 2007).

Correlational Research

According to Inigo Jones and Bartlett (2011), in correlational inquiry, investigator are interested in the kinship between variable star s. Research worker ask if one (the fencesitter variable) links to or even causes a behaviour or reaction in another (the dependant variable). The design provides kinship and the strength of relationship between two variable star. Correlational research is used to resolution relational type inquiry. Object lesson of divisor-relating doubt could include “What is the relationship between depression and self-annihilation among teenagers?” or “What is the relationship between need and example behavior?”. However, before these questions can be answered, the factors or variables have to be described by either a prior descriptive story study or synthesis of published literature (Jones & Bartlett, 2011). If, for example, we were interested in whether boy or miss choose more free-option activities in an early childhood centre, we might ask how the independent variable does (for example, sexuality ) relate to the phenomenon of interest (for example, free-choice activities in an early childhood centre).

According to Fraser Wellness Say-so (2011), an vantage of using correlational research is that this method acting provides an evaluation of strength and direction of kinship between variable quantity. Correlational studies also provide for a basis for experimental studies to follow. The primary disadvantage with this pattern is that no conclusions can be made regarding causality, just that there is a kinship between the mental test ed variables. Predictive studies also convulsion under this level, and they describe the human relationship between prognosticator variables and the dependent variable (outcome measure). Data from correlational studies would primarily include descriptive statistics as described above and correlations. For example, correlational analytic thinking would test whether there is a relationship between clinical depression and suicide among teenagers, whether it is a positive or negative relationship, and how strong that relationship is (Fraser Health Agency , 2011).

An example of this design is a study completed by Al-Kandari, VidAL , and Thomas (2008) examining the relationship between a health promoting spirit -mode and body mountain index among college students in Kuwait . The study sample included all 350 nursing students enrolled in the AND program during one semester. Walker’s Health Promoting Lifestyle Questionnaire (HPLP-II) was administered to assess health promoting attitudes and behaviors. A Pearson’s correlation was done to discovery out the relationship of the floor s of enrollment with the HPLP-II and Body mass index. Findings included a significant positive correlation between the BMI and the level of nursing course. That is, as students progressed in their nursing courses, their BMI increased (Al-Kandari, et al., 2008).

Experimental Research

In experimental research, investigator manipulate one or more variable (s) to establish cause-effect family relationship between dependent and mugwump variable star (Inigo Jones & Bartlett, 2011). The researcher ascendence ler the independent variable and study conditions and randomly assigns treatment to study participant or subjects. To be considered experimental level research, there must be random selection and/or random assignment of subjects, control/ manipulation of the treatment/intervention, and include treatment and control chemical group (Jones & Bartlett, 2011). According to Fraser Health Authority (2011), the different eccentric s of randomisation in experimental research design include simple, blocked where match treatment numbers at certain equally spaced decimal point in the sequence of subject assignments are established and stratified where randomisation occurs within specified strata (for example, sex, age groups, disease stage). Another type of randomization is randomized command trial (RCT) where two or more groups are randomly assigned treatments and a baseline measure is taken. Lastly, is the Billet -exam Only Control Group Pattern where treatment is randomly assigned to two or more groups and the outcome is measured (Fraser Health Authority, 2011).

According to Fraser Health Dominance (2011), another type of experimental inquiry is the quasi-experimental innovation which lacks random assignment to study treatment and where the independent variable quantity is only partially under the mastery of the researcher. This conception is used to examine cause and core by ruling out plausible alternative explanations (Fraser Health Dominance , 2011). An example of this type of research design is the Pre-test Military post Post-test Non-Combining weight Grouping where both a mastery mathematical group and an experimental group are compared but groups are formed out of convenience (rather than randomization). Experimental designs are the most difficult to implement since it takes more sentence and money to produce a randomized sample (Jones & Bartlett, 2011). Also, it may not be ethically possible to withhold treatment from the control group, thus preventing a true experimental design. This research method is one of the most difficult, requiring rigorous design and a great trade of expense, especially for larger experiments. The other trouble , where real life organisms are used, is that pickings something out of its cancel surroundings can seriously affect its demeanour (Jones & Bartlett, 2011).

An example of an experimental study provided by Hoadley (2009) compared the event of David Low and highschool -faithfulness pretence in encyclopedism advanced cardiac life support (ACLS). This study compared result of two ACLS classes on measures of knowledge and resuscitation skills. One of the four hypotheses was, “ACLS course participant will have significantly higher rafts on the ACLS posttest when they experience computerized, high-fidelity simulation rather than instructor-led, low-fidelity simulation for resuscitation practice session (Hoadley, 2009).” The theoretical framework for the study was John John Dewey ’s experiential encyclopaedism philosophy. The study sampling was made up of 53 healthcare provider randomly assigned into experimental or restraint groups. For the sample hypothesis given above, T-tests were done to test for significant departure s. No significant difference was found between the high-fidelity versus the low-fidelity mode of instruction on ACLS posttest scores. Another example is when you are testing a new fall preventive syllabus within your hospital where it would require you to obtain a baseline fall rate before the political program and then again after full implementation of the program. Statistically you could compare the rates of falls before the new program with the rate of falls after the new program. Your unit of measuring would be numbers and would lend itself to a quantitative design (Hoadley, 2009).

Another example is a survey by Rosenthal and Jacobson (1968), who as part of a course of study of research into the impact of self-fulfilling prophecies (for example, where someone’s beliefs or expectations about someone else influence how the latter behaves), they conducted a research into the question of whether teacher s’ expectations of their scholarly person’ ability in fact influence the schoolhouse operation of the latter. The research was conducted in a lower-division neighborhood in the United States of America with a high spirit level of children from minority group backdrop . In the spring of 1964, all the educatee completed a trial that was portrayed as a means of identifying ‘spurters’—that is, student who were likely to excel faculty member ian ally. At the get-go of the following academic twelvemonth, all the instructor were notified of the 6 senses of name of the students who had been identified as spurters. In fact, 20 per cent of the school children had been identified as spurters. However, the students had actually been administered a conventional Intelligence quotient test and the so-called spurters had been selected randomly. The test was re-administered eight months after the original one. The generator were then able to comparability the difference between the spurters and the other students in terminus of changes in various criterion of academic execution, such as I.Q. mark, reading ability, and intellectual curiosity. Since there was no grounds for there being any difference in ability between the spurters and the rest, any indications that the spurters did in fact differ from their equal could be attributed to the fact that the teacher had been led to expect the former would perform better. The Synonyms/Hypernyms (Ordered by Estimated Frequency) of noun finding show that such difference of opinion did in fact exist, but that the differences between the spurters and their compeer tended to be concentrated in the first two or three years of school . In other words, the grounds for a teacher expectancy effect was patchy. Nonetheless, this is an influential experimentation that is widely believed to provide firm evidence of a teacher expectancy effect (Hammersley, 2011: 106–9).

Conclusion

In this paper we have discussed what quantitative enquiry is as well as the different quantitative inquiry designs and what influences the alternative of their use. Quantitative enquiry is about explaining phenomena by assembling quantitative data which are analyzed using mathematically based method acting (Kothari, 2014). The fact that the data have to be quantitative does not mean that they have to be naturally available in quantitative form. In this bailiwick three quantitative inquiry method acting /feeler ing have been identified, that is, descriptive research, correlational research and experimental research. The study has also identified practical lotion of each of the three quantitative research approaches and therefore it concludes that if a pragmatic approach to research method is taken, it is important to discovery out what form of inquiry s are best answered using quantitative as opposed to qualitative methods. The main character of research question that quantitative research is particularly suited to find an answer to includes when a quantitative answer is expected, when studying a numerical modification in phenomena, when explaining a phenomenon and when testing hypotheses (Creswell, 2013).