Writing a quantitative research question

Formulating a quantitative research question can often be a difficult task.  When composing a research question, a researcher needs to determine if they want to describe data, compare differences among groups, assess a relationship, or determine if a set of variables predict another variable.  The type of question the researcher asks will help to determine the type of statistical analysis that needs to be conducted.  It is also important to consider what specific variables need to be assessed when writing a research question.  The researcher must be certain all variables are quantifiable, or measurable. Measuring variables can be as simple as having participants report their age or as involved as having participants answer survey questions that make up a reliable instrument.  Some examples of different types of research questions are presented below:

Descriptive:

Describe the teachers’ perceptions of the newly implemented reading assessment program.

The goal of a descriptive research question is to describe the data.  The researcher cannot infer any conclusions from this type of analysis; it simply presents data.  Descriptive questions do not have corresponding null and alternative hypotheses because the researcher is not making inferences.  Descriptive studies can be conducted on categorical or continuous data.

Comparative:

Are there differences in students’ grades by gender (male vs. female)?

Are there differences in job level (entry vs. mid vs. executive) by gender (male vs. female)?

Comparative questions can be assessed using a continuous variable and a categorical grouping variable, as well as with two categorical grouping variables.  They type of analysis will vary depending on the types of data.

Relationship:

Is there a relationship between age and fitness level?

Is there a relationship between ice cream sales and temperature at noon?

Questions that assess relationships do not require a definitive independent and dependent variable, but two variables are required; they can be considered variables of interest as opposed to independent and dependent variables.  Data used for this type of analysis can be dichotomous, ordinal, or continuous.  They type of analysis will vary depending on the types of data. 

Predictive:

Do age, gender, and education predict income?

Does a pitcher’s ERA predict the number of wins the team has?

Predictive questions have a definitive independent and dependent variable.  Typically, the independent variable should be continuous or dichotomous, but nominal and ordinal variables can be used.  When nominal and ordinal variables are used as predictors, they must be dummy coded.  Like the independent variable, the dependent variable is typically continuous or dichotomous, but can also be ordinal or nominal.  The type of analysis that is appropriate will vary based upon the type of data.

Practice MRF

You may be saying the MRF stands for “Man, Research Frustrating.” For those struggling with Capella’s BMGT8032: Survey of research methods, or for other dissertation students working on their proposal, here are a few thoughts. 

Research questions 1.6.  Your research questions need to have clear measures, you have to be able to get in touch with the participants, and they have to be stated in statistical language.   If you don’t have these three things, you don’t have answerable research questions. 

Sample size 2.2.  Sample size is a tricky thing, and maybe the order of writing has something to do with this.  Capella has this section as 2.2, which talks about the sample—fair enough.  However, since the preponderance of dissertations use a power analysis, and the power analysis is different based on the statistics used, the sample size justification (section 2.2) should go after, not before, the data analysis plan 2.5.  The best thing to do is to make sure you have the correct analysis, then use G-power (which is free) or go to our membership website page basic-membership for a write-up ($29). 

Measurement 2.3: First of all, this will become part of your dissertation, so make sure that you have constructs that are measurable.  If you are the first person to measure a particular construct, expect a few extra months to pilot test the instrument, then you still have to assess the reliability and validity of the new instrument.  Don’t reinvent the wheel—find a reliable and valid instrument that exists. Worst case, adapt a reliable and valid instrument, and use a change cross-walk in the appendix to show how your adaptation is different.

Data analysis plan 2.5.  The data plan is comprised of three components: which analyses are appropriate to assess your research questions, what are the assumptions of the selected analyses, and a justification of why the analyses were select.  The appropriate analysis is selected based on the way the research question is phrased (i.e., “difference” questions presume ANOVA type analyses) and the level of measurement of the variables (i.e., ANOVAs presume an interval or ratio level dependent variable and a nominal level independent variable).  The assumptions of an analysis can be found on our website (www.StatisticsSolutions.com) or elsewhere on the web.  And finally, the justification of the analysis combines the above two points by simply stating that given the research question phrasing and the level of measurement, this particular statistical test is appropriate. 

Certainly, any questions, feel free to call us (877) 437-8622 or email us info@StatisticsSolutions.com

Dissertation Methodology

Dissertation writing is a very complex and crucial task. And yet, finishing one’s dissertation is essential because a student does not get a degree without it. Writing a dissertation requires a student to do an immense amount of hard work. It also requires them to be very efficient. Not only does dissertation writing require hard work and dedication, it requires knowledge of how to actually go about writing a dissertation. Thus, it is especially difficult and problematic for students who are writing their dissertations for the first time. In other words, even if students are putting in the hard work necessary, they can still get very frustrated because many of these “first timers” do not even know how to begin their dissertation.

Students would benefit greatly from understanding that in the times when nothing seems to make sense, the best way to overcome the confusion is to plan things out. In the case of writing a dissertation, referring to a first chapter of dissertation methodology can always help as it can ease the overwhelming confusion students may feel when they face the task of writing their dissertation. Once a student has a clean chart of dissertation methodology in front of him or her, things start to make sense. Dissertation methodology is a chapter that carries the most important and necessary information about the subject of one’s research. Dissertation methodology generally includes the following steps:

• Participants
• Procedures
• Instruments and
• Data Analysis

The first thing that a student must do is decide the nature of his/her dissertation. He/she must decide whether his/her research is Qualitative or Quantitative? When deciding between Qualitative and Quantitative, one must consider a number of issues. Neither of the two methodologies is ‘simpler’ or ‘better’. The decision is merely based on what one wants the end of his/her dissertation to be. To decide the methodology, the student has to see the target audience and decide which methodology will easily help this audience understand the steps of the project. It also depends on the student’s research questions and targets. After choosing the approach, the student can analyze collected data. This can be done through methods like grounded theory, domain analysis, analytic induction, factor analysis, or cluster analysis etc. The dissertation methodology should be based on getting the most useful information in the most effective and practical manner.

Going through the following steps will make writing a Dissertation Methodology chapter much easier:

• Sketch out a plan as an overview of the way your Dissertation Methodology would come out. It is fruitful to know your next step when you finish the one before it, as it helps in not missing out on any of the important aspects of the methodology.
• Try to be patient, careful and attentive while writing those steps.
  
• Time management is a very important aspect at this point. Planning while you are well aware of the vast amount of other things that you have to take care of is key.
• Whatever information you gather, you should always cross check for its correctness.
• While gathering the theoretical and literary data for dissertation methodology, you should bear in mind that the sources of that data should be authentic and clear to you.
• It is always important to be logical and up to the mark in your methodology. This holds true, for instance, while giving examples and dividing parts and paragraphs.
• Analyze your practical calculation and theory very carefully.
  

After finishing your Dissertation Methodology chapter, you will have a much more focused idea for your dissertation. Designing the most important part of your dissertations will clearly make the task of your actual dissertation very easy and clear. Additionally, it will help you in organizing your skills and knowledge for writing the dissertation.

Research Methodology

Research Methodology is a critical component of any research exercise as it can make the difference between a completely irrelevant and a completely relevant exercise. Frequently, the research methodology underlying a multi-million dollar research project can make the difference between completely accurate and completely inaccurate results, although the underlying methods or processes may have been done accurately.

Research methodology is thus the foundation or general rules that determine the accuracy and validity of any research activity. It’s important to understand the difference between the terms ‘methodology’ and ‘method’, as the former refers to the general rules and guidelines pertaining to a set of methods, and explains why a specific strategy to address a specific research question is to be applied. Research methodology can cover the following three key areas of research:

· Survey design

· Data collection

· Data analysis

Research methodology will determine how a specific survey is to be designed and how large the sample population should be, in addition to other practical questions such as which scaling method to use, what kind of target population to which to address the survey, how the survey is to be disseminated and so on. Each of these components will constitute a larger body of knowledge and have its own impact on the outcome and validity of the survey. For instance, using a Likert scale as opposed to a True-False type of question can lead to substantial variations in the accuracy of the survey.

In the same fashion, telephone interviews versus mail-response interviews each has its own set of pros and cons. Data collection is thus another important aspect of the research methodology. Data analysis is an extremely important aspect to consider when conducting research. There are a number of different methods that can be applied to similar problems based on the type of response (multiple choice, true false, numerical, etc.), sample size and expected outcome. Furthermore, each type of test will have its’ own pros and cons. For instance, in testing significance of variables, parametric (t-test, z-test, ANOVA, etc.) or non-parametric (chi-square, Kruskal-Wallis, Wilcoxon signed-rank, etc.) tests may be used. Based on the specific features of a dataset, a specific set of methods will have to be adopted in order to produce the most accurate possible result.

Types of research methodologies

Research is typically categorized in two forms:

1. Qualitative: where variables are not quantified and judgment, inference and interpretation are required along specific qualitative analysis expertise, to generate results

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2. Quantitative: where variables are quantified and scientific methods can be applied to generating a precise result which can be applied to building quantifiable results

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Given the nature of each type of research, different research methodologies are applied to each type; for instance, while a qualitative research project uses techniques such as case study, ethnography, and discourse analysis, quantitative methodologies use experiments, interviews, surveys and the like. Each research methodology, in addition to prescribing specific methods for design, data collection and analysis, provides general guidelines as to applicability and validity.

In general, qualitative research methodologies share the following common characteristics:

• They generally take place in a social setting
• Involve social observation and interaction
• Rely on inference and interpretation

Its drawbacks include but are not limited to the following:

• Results are based on interpretation and inference which may lead to a significant ‘error’ possibility in across the board application
• Given the significant social component of such studies, a lot of variability may be present in the results due to the presence of researcher bias, skill and participant composition

Quantitative research generally share the following characteristics:

• Typically rule based, involve a substantial amount of calculation as opposed to interpretation
• Frequently based on values assigned to a number of qualitative aspects
• Produce a quantifiable, measurable result that can be applied to a number of different settings.

Drawbacks

• A number of variables such as preference, value and importance cannot be easily quantified
• Valuable input from the researcher is minimized, shifting bias error to the participant
• Quantifiable results are not always ‘generalized’ and are very specific to a certain set of variables and conditions.

Above all, research methodology helps set the reasonable boundaries of a research project at the start, and anticipate the various problems that may be encountered during the activity. In addition to the said components, research methodology can be greatly influenced by the judgment, skills and beliefs of the researcher as well. There may be wide variations in the adopted methodology as time, funds and other resources permit.

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