Deciding the research questions and hypothesis of a study is an essential aspect of conducting a quantitative study. This is because it determines the direction unto which the study will follow as well as the how accurate the results will be. A hypothesis is a statement that explains the relationship between two or more variables. It is during the research study that this statement is tested, and the connection is proved within the particular context of the study. On the other hand, a research question is similar to a hypothesis as it addresses an aspect or concept of a hypothesis but in question format. It is a crucial element in every research study as it defines the direction and purpose of the study. This paper explains the differences between the various type of quantitative research question and hypothesis.
Quantitative Research Questions
The beginning of a research process occasionally begins with an interest in a particular topic ( Creswell & Clark, 2017). Similarly, the familiarity with the specific subject under study plays an essential role in defining the most appropriate research questions that will be used for the study. Thus, quantitative research questions are well organized worded questions that address specific concept, describes the purpose of the study and explores the relationship between variables in a research study ( McCusker & Gunaydin, 2015). In some situations, they also help in addressing the magnitude of a single variable in the study. For instance, “What is the level of participation of university students in the campaign against HIV/AIDS?. In this situation, the focus of the research question is not only to explore the relationship between variables but to find out the level/ magnitude of the participants in the campaign.
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There are various types of research questions that guide a researcher when conducting a particular study. However, quantitative research is guided by three main research questions namely: descriptive, comparative, and relationship-based research questions. Descriptive research questions are designed to systematically and accurately uncover the facts and characteristics of a particular population or the subject area under interest ( Bernard, 2017). The researcher can discover new meaning through the respondent’s response to the specific question or variable. A descriptive research question helps in quantifying the particular variable(s) the researcher is interested in on a large scale. These variables may be phenomena, characteristics or the frequency of the variable under interest. Besides, the main aim of a descriptive research question is to describe the data. The researcher cannot infer a conclusion by analyzing that data collected, as detailed questions do not have the null and alternative hypothesis that play an essential role when it comes to making inferences. Some of the most general descriptive research questions include: "how often do students buy mobile apps for study purposes?” In this descriptive research, the variable is the number of mobile apps and the demographic is the students. Another example of a descriptive research question is “Why do Asian-America have high performance is mathematics related courses as compared to other groups of students?" The main aim of this research question is to discover relations between the variable (mathematics related subjects).
Quantitative relationship-based research questions are also known as causal based research questions. These types of questions in a quantitative study work by helping the researcher understand how one particular variable influences the other variable. Relationship-based research questions often do not require either a definitive dependent or independent variable to assess relationships, but two variables must be available. Data used for this type of analysis can be dichotomous, ordinal, or continuous. The relationship-based question includes, what is the relationship between low salary and high turnover rates among employees. In the example, the dependent variable is job satisfaction while the independent variable is the salary. The demographic under research is the employees. Relational questions are also designed to determine if changing one variable has a measurable effect on other sets of variables under study. An example of such a relational based question could be “Does increase in the average salary of employees affect their overall performance in the organization immediately?.
Comparative research questions in a quantitative research study are used to analyze the differences between two or more variables, concepts or groups. A typical comparative question often begins with the phrase (what is) or the respondent asking for the “difference between” a particular concept or variable. All pertinent research questions must contain a dependent variable. For instance, what is the difference in high caloric intake between men and women in the United States? In this example, the daily caloric intake is the dependent variable. Comparative research questions have at least groups.The two groups are mostly used for comparison purposes and highlight /reflect the underlying condition (dependent variable).
The above examples of types of quantitative research questions illustrate that the language of the research question may change depending on what a researcher may want to study in a particular group of people. However, the dependent and independent must may present as well as the controlled environment/demographics to conduct a compelling study that the results are precise and accurate knowledge.
Quantitative Hypothesis
Before the beginning of research work, one of the most important consideration is the formulation of a research question as well as a hypothesis. While a researcher can conduct a proper research study without necessarily having to formulate a hypothesis, it is essential for an excellent researcher to have one as it provides direction and clarity. This means that the researcher can narrow down on the focus of the research problem, bringing specificity to the research work.
According to Bernard (2017), a hypothesis is clearly defined as a testable proposition /statement that describes the relationships between two or more variables. McCusker and Gunaydin(2015) assert that a hypothesis is a well-written statement that can be either be proven or disproved by valid and reliable data. According to the above definition, a hypothesis is a proposition that is formulated before the beginning of the actual research study to help the researcher to focus on s specific scope of a research problem. Similarly, its validity is unknown, and it is tested during the actual study using reliable data. The data can either approve or disapprove the proposal.
In quantitative studies, a hypothesis is a prediction that a researcher makes about the expected outcomes of relationships among variables ( Bryman & Bell, 2015) . This is usually formulated in advance using the existent knowledge that the researcher might have acquired on a particular subject. During the actual study, the researcher employs statistic procedures that help in approving or disapproving the formulated hypothesis. The results obtained are seen as an advancement of knowledge in that field of research. This knowledge may help other researchers who might be interested in testing the relationship is also in different contexts. Just like research questions, a quantitative hypothesis is derived from theories and research that has already been conducted on the subject. Thus, a quantitative prediction is obtained from to the literature review undertaken already on the subject matter. For example, there has been research on the number of children involved in child labor in African countries. In this study, the research question could be: what is the link between school children drop out, and children involved in forced labor, the hypothesis, on the other hand, could be: As the number of school children drops out increases, the number of forced child labor increases in children aged 10-12 years. In this example, the research question aims at studying at the relationships between variables while the hypothesis seeks to collect data to draw inferences about the population. Thus, a prediction come from existing theory, the belief itself, an observation which involves collecting the data and lastly confirmation ( Creswell& Creswell, 2017).
Hypothesis just like research questions usually includes the independent variable, dependent variable, the outcome as well as the demographics. In the above example, the dependent variable is forced child labor, the independent variable is school dropout, and the demographics are children. The outcome that has already been predicted is the school dropout increasing child labor. In a hypothesis, the independent and the dependent variable may have a positive or a negative association depending on the direction of their relationship. In positive association, the two variables under study are positively related, and they change in the same direction. Thus, if one variable decreases, the other variable decreases, and vice versa. An example of such a hypothesis could be higher internet addiction increased the likelihood of scoring poor grades. On the other hand, in a negative association, the two or more variables in a hypothesis change in the opposite direction or are negatively associated. Thus, if one variable decreases the other one increases and vice versa. For example, sleep-deprived students are at the increased likelihood of not concentrating in class.
According to Creswell and Creswell (2017), there is only one type of hypothesis, that is, research hypothesis. However, recent studies in the field of statistical analysis show that a research hypothesis can be categorized into two main categories-null and alternate hypotheses. The null hypothesis in quantitative research is also referred to as the statistical hypothesis and is often noted as HO (H zero) or HN (H null). This type of hypothesis expresses a variable relationship that has either been proved right or has not yet been tested. This type of hypothesis affirms that there is no relationship between two or more variables, as it has already been predicted in the research hypothesis. In quantitative research, the researcher usually concludes that the null hypothesis has been rejected in favor of the alternative hypothesis. Alternatively, the study concludes that the null hypothesis has been denied. When conducting quantitative research, when the null hypothesis is rejected, it does not necessarily mean that the null hypothesis is valid. According to Creswell and & Clark (2017 ), it only shows that the context of the particular study under research did not have enough evidence to approve or disapprove the null hypothesis.
The following example is used to determine how a null hypothesis can be derived. For instance, a researcher wants to research the prevalence of IT literacy in a particular community concerning gender differences. Based on this research question, various hypotheses can be constructed.
60 percent of the male population and 40 percent of the female population are computer literate.
A significant number of the male population is computer literate as compared to the female population.
There is no significant difference in the number of the male and female population who are computer literate.
From the example, the third hypothesis shows that there is no difference regarding computer literacy when it comes to both genders, and is called a null hypothesis.
The alternative or direction hypothesis is also another form of the hypothesis is that recognized in statistics. As compared to the null hypothesis, this type of hypothesis shows a difference or any effect in between two or more variables that have been predicted by the researcher. The alternative hypothesis follows the rules of statistics or science, as it refutes the null hypothesis before even claiming to support an alternative hypothesis. According to Bryman, & Bell (2015) , an alternative hypothesis can either be directly or non-directional.
In the directional hypothesis, the researcher uses prior research on the subject by using the literature review to predict the expected outcome (Creswell& Creswell, 2017). For example, the researcher may predict that a particular population A is likely to have a higher probability of having a specific illness that population B. In this example, on the dependent variable, population A is expected to change on the higher side as compared to the population B when the actual research is conducted. The following example further illustrates a directional hypothesis. In research on the prevalence of computer literacy on a community comprising of both men and women, the results of the study showed that men are likely to be more computer literate as compared to women. Besides, Men are more interested in IT related activities as compared to women. Hypothesis number 3 showed that men have technical expertise as compared to women. The results show that the hypothesis that the researcher will develop will likely follow that direction.
The non-directional hypothesis also makes a prediction based on existing literature on the particular subject under research. However, the difference regarding percentage higher or lower is usually not specified as the previous literature had also not included. In most cases, the non-direction hypothesis only uses the word differently to show the differences between the two variables.
In conclusion, the development of research questions and hypothesis is an essential aspect of any quantitative study. The success of quantitative research is dependent on how the researcher formulates the research questions and hypothesis. In quantitative studies, the researcher includes the variables that are described, related or categorized into one group. The independent and dependent variables are measured separately. In a quantitative study, researchers often use questions to formulate the best hypothesis. While designing the relevant research question and hypothesis can be a difficult task for a researcher. The paper has helped in outlining the differences between a hypothesis and a research question with the aim of guiding future researchers.
References
Bernard, H. R. (2017). Research methods in anthropology: Qualitative and quantitative approaches . Rowman & Littlefield.
Bryman, A., & Bell, E. (2015). Business research methods . Oxford University Press, USA.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approach . Sage publications.
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research . Sage publications.
McCusker, K., & Gunaydin, S. (2015). Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion , 30 (7), 537-542.
