How are statistical research questions for quantitative analysis written? This article provides five examples of statistical research questions that will allow statistical analysis to take place.
In quantitative research projects, writing statistical research questions requires a good understanding and the ability to discern the type of data that you will analyze. This knowledge is elemental in framing research questions that shall guide you in identifying the appropriate statistical test to use in your research.
Thus, before writing your statistical research questions and reading the examples in this article, read first the article that enumerates thefour types of measurement scales. Knowing the four types of measurement scales will enable you to appreciate the formulation or structuring of research questions.
Once you feel confident that you can correctly identify the nature of your data, the following examples of statistical research questions will strengthen your understanding. Asking these questions can help you unravel unexpected outcomes or discoveries particularly while doing exploratory data analysis.
Table of Contents
Five Examples of Statistical Research Questions
In writing the statistical research questions, I provide a topic that shows the variables of the study, the study description, and a link to the original scientific article to give you a glimpse of the real-world examples.
Topic 1: Physical Fitness and Academic Achievement
A study was conducted to determine the relationship between physical fitness and academic achievement. The subjects of the study include school children in urban schools.
Statistical Research Question No. 1
Is there a significant relationship between physical fitness and academic achievement?
Notice that this study correlated two variables, namely 1) physical fitness, and 2) academic achievement.
To allow statistical analysis to take place, there is a need to define what is physical fitness, as well as academic achievement. The researchers measured physical fitness in terms ofthe number of physical fitness teststhat the students passed during their physical education class. It’s simply counting the ‘number of PE tests passed.’
Statistical Research Questions: 5 Examples for Quantitative Analysis
On the other hand, the researchers measured academic achievement in terms of a passing score in Mathematics and English. The variable is thenumber of passing scoresin both Mathematics and English.
Both variables are ratio variables.
Given the statistical research question, the appropriate statistical test can be applied to determine the relationship. A Pearson correlation coefficient test will test the significance and degree of the relationship. But the more sophisticated higher level statistical test can be applied if there is a need to correlate with other variables.
In the particular study mentioned, the researchers usedmultivariate logistic regression analysesto assess the probability of passing the tests, controlling for students’ weight status, ethnicity, gender, grade, and socioeconomic status. For the novice researcher, this requires further study of multivariate (or many variables) statistical tests. You may study it on your own.
Most of what I discuss in the statistics articles I wrote came from self-study. It’s easier to understand concepts now as there are a lot of resource materials available online. Videos and ebooks from places like Youtube, Veoh, The Internet Archives, among others, provide free educational materials. Online education will be the norm of the future. I describe this situation in my post aboutEducation 4.0.
The following video sheds light on the frequently used statistical tests and their selection. It is an excellent resource for beginners. Just maintain an open mind to get rid of your dislike for numbers; that is, if you are one of those who have a hard time understanding mathematical concepts. My ebook onstatistical tests and their selectionprovides many examples.
Source: Chomitz et al. (2009)
Topic 2: Climate Conditions and Consumption of Bottled Water
This study attempted to correlate climate conditions with the decision of people in Ecuador to consume bottled water, including the volume consumed. Specifically, the researchers investigated if the increase in average ambient temperature affects the consumption of bottled water.
Statistical Research Question No. 2
Is there a significant relationship between average temperature and amount of bottled water consumed?
In this instance, the variables measured include theaverage temperature in the areas studiedand thevolume of water consumed. Temperature is aninterval variable,while volume is aratio variable.
In this example, the variables include theaverage temperatureandvolume of bottled water. The first variable (average temperature) is an interval variable, and the latter (volume of water) is a ratio variable.
Now, it’s easy to identify the statistical test to analyze the relationship between the two variables. You may refer to my previous post titledParametric Statistics: Four Widely Used Parametric Tests and When to Use Them. Using the figure supplied in that article, the appropriate test to use is, again, Pearson’s Correlation Coefficient.
Source: Zapata (2021)
Topic 3: Nursing Home Staff Size and Number of COVID-19 Cases
An investigation sought to determine if the size of nursing home staff and the number of COVID-19 cases are correlated. Specifically, they looked into the number of unique employees working daily, and the outcomes include weekly counts of confirmed COVID-19 cases among residents and staff and weekly COVID-19 deaths among residents.
Statistical Research Question No. 3
Is there a significant relationship between the number of unique employees working in skilled nursing homes and the following:
- number of weekly confirmed COVID-19 cases among residents and staff, and
- number of weekly COVID-19 deaths among residents.
Note that this study on COVID-19 looked into three variables, namely 1) number of unique employees working in skilled nursing homes, 2) number of weekly confirmed cases among residents and staff, and 3) number of weekly COVID-19 deaths among residents.
We call the variablenumber of unique employeestheindependent variable, and the other two variables (number of weekly confirmed cases among residents and staffandnumber of weekly COVID-19 deaths among residents) as thedependent variables.
This correlation study determined if the number of staff members in nursing homes influences the number of COVID-19 cases and deaths. It aims to understand if staffing has got to do with the transmission of the deadly coronavirus. Thus, the study’s outcome could inform policy on staffing in nursing homes during the pandemic.
A simple Pearson test may be used to correlate one variable with another variable. But the study used multiple variables. Hence, they producedregression modelsthat show how multiple variables affect the outcome. Some of the variables in the study may be redundant, meaning, those variables may represent the same attribute of a population.Stepwise multiple regression modelstake care of those redundancies. Using this statistical test requires further study and experience.
Source: McGarry et al. (2021)
Topic 4: Surrounding Greenness, Stress, and Memory
Scientific evidence has shown that surrounding greenness has multiple health-related benefits. Health benefits include better cognitive functioning or better intellectual activity such as thinking, reasoning, or remembering things. These findings, however, are not well understood. A study, therefore, analyzed the relationship between surrounding greenness and memory performance, with stress as a mediating variable.
Statistical Research Question No. 4
Is there a significant relationship between exposure to and use of natural environments, stress, and memory performance?
As this article is behind a paywall and we cannot see the full article, we can content ourselves with the knowledge that three major variables were explored in this study. These are 1) exposure to and use of natural environments, 2) stress, and 3) memory performance.
Referring to the abstract of this study,exposure to and use of natural environmentsas a variable of the study may be measured in terms of the days spent by the respondent in green surroundings. That will be a ratio variable as we can count it and has an absolute zero point. Stress levels can be measured using standardized instruments like thePerceived Stress Scale. The third variable, i.e., memory performance in terms of short-term, working memory, and overall memory may be measured using a variety ofmemory assessment tools as described by Murray (2016).
As you become more familiar and well-versed in identifying the variables you would like to investigate in your study, reading studies like this requires reading the method or methodology section. This section will tell you how the researchers measured the variables of their study. Knowing how those variables are quantified can help you design your research and formulate the appropriate statistical research questions.
Source: Lega et al. (2021)
Topic 5: Income and Happiness
This recent finding is an interesting read and is available online. Just click on the link I provide as the source below.
The study sought to determine if income plays a role in people’s happiness across three age groups: young (18-30 years), middle (31-64 years), and old (65 or older). The literature review suggests that income has a positive effect on an individual’s sense of happiness. That’s because more money increases opportunities to fulfill dreams and buy more goods and services.
Reading the abstract, we can readily identify one of the variables used in the study, i.e., money. It’s easy to count that. But for happiness, that is a largely subjective matter. Happiness varies between individuals. So how did the researcher measured happiness? As previously mentioned, we need to see the methodology portion to find out why.
If you click on the link to the full text of the paper on pages 10 and 11, you will read that the researcher measured happiness using a 10-point scale. The scale was categorized into three namely, 1) unhappy, 2) happy, and 3) very happy.
An investigation was conducted to determine if the size of nursing home staff and the number of COVID-19 cases are correlated. Specifically, they looked into the number of unique employees working daily, and the outcomes include weekly counts of confirmed COVID-19 cases among residents and staff and weekly COVID-19 deaths among residents.
Statistical Research Question No. 5
Is there a significant relationship between income and happiness?
Source: Måseide (2021)
Now the statistical test used by the researcher is, honestly, beyond me. I may be able to understand it how to use it but doing so requires further study. Although I have initially did some readings on logit models, ordered logit model and generalized ordered logit model are way beyond my self-study in statistics.
Anyhow, those variables found with asterisk (***, **, and **) on page 24 tell us that there are significant relationships between income and happiness. You just have to look at the probability values and refer to the bottom of the table for the level of significance of those relationships.
I do hope that upon reaching this part of the article, you are now well familiar on how to write statistical research questions. Practice makes perfect.
Chomitz, V. R., Slining, M. M., McGowan, R. J., Mitchell, S. E., Dawson, G. F., & Hacker, K. A. (2009). Is there a relationship between physical fitness and academic achievement? Positive results from public school children in the northeastern United States.Journal of School Health,79(1), 30-37.
Lega, C., Gidlow, C., Jones, M., Ellis, N., & Hurst, G. (2021). The relationship between surrounding greenness, stress and memory.Urban Forestry & Urban Greening,59, 126974.
Måseide, H. (2021). Income and Happiness: Does the relationship vary with age?
McGarry, B. E., Gandhi, A. D., Grabowski, D. C., & Barnett, M. L. (2021). Larger Nursing Home Staff Size Linked To Higher Number Of COVID-19 Cases In 2020: Study examines the relationship between staff size and COVID-19 cases in nursing homes and skilled nursing facilities. Health Affairs, 40(8), 1261-1269.
Zapata, O. (2021). The relationship between climate conditions and consumption of bottled water: A potential link between climate change and plastic pollution. Ecological Economics, 187, 107090.
© P. A. Regoniel 12 October 2021
Suggested citation: Patrick A. Regoniel, PhD (October 12, 2021). Statistical Research Questions: Five Examples for Quantitative Analysis. Research-based Articles. Retrieved on June 1, 2023 from https://simplyeducate.me/2021/10/12/statistical-research-questions/
Put simply, it's the easiest way to quantify the particular variable(s) you're interested in on a large scale. Common descriptive research questions will begin with “How much?”, “How regularly?”, “What percentage?”, “What time?”, “What is?”What are the 5 research questions? ›
- What information do I need?
- Where do I find information?
- Which information can I trust?
- How can I use new information in my writing?
- How do I use information ethically?
It all comes down to using the right methods for statistical analysis, which is how we process and collect samples of data to uncover patterns and trends. For this analysis, there are five to choose from: mean, standard deviation, regression, hypothesis testing, and sample size determination.What questions does a quantitative research answer? ›
Quantitative research can help you answer questions such as “how many” and “how often” and is invaluable when putting together a business case before launching a new product or service, or proposing changes to existing ones.What are 5 examples of quantitative research? ›
- Descriptive Research Design.
- Survey Research.
- Correlational Research Design.
- Quasi-experimental Research Design.
- Experimental Research Design.
- What effect does social media have on your mind?
- What effect does daily use of Twitter have on the attention span of 12-16 year-olds?
- Choose your starting phrase.
- Identify and name the dependent variable.
- Identify the group(s) you are interested in.
- Decide whether the dependent variable or group(s) should be included first, last or in two parts.
- Include any words that provide greater context to your question.
- How can standardized tests improve education?
- Does college graduates make more money?
- Should education be cheaper?
- How will modern technologies change the way of teaching in the future?
- The creation of particular learning methods for blind children.
- Social networking and school.
The five basic methods are mean, standard deviation, regression, hypothesis testing, and sample size determination.What is an example of a quantitative data analysis? ›
Quantitative data is data that can be counted or measured in numerical values. The two main types of quantitative data are discrete data and continuous data. Height in feet, age in years, and weight in pounds are examples of quantitative data.
There are significant tests, like t-test, f-test, z-test, chi square test, etc. that are referred to as quantitative techniques in quantitative analysis.What is a quantitative analysis question? ›
Quantitative research questions are objective questions that provide detailed knowledge about a research topic. The data obtained with quantitative research questions are numerical that can be examined statistically.What are quantitative questions? ›
Quantitative survey questions are defined as objective questions used to gain detailed insights from respondents about a survey research topic. The answers received for these quantitative survey questions are analyzed and a research report is generated on the basis of this quantitative data.What are the four types of quantitative research questions? ›
There are four main types of Quantitative research: Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research.What is quantitative research and give 2 examples? ›
Quantitative research collects information from existing and potential customers using sampling methods and sending out online surveys, online polls, and questionnaires, for example. One of the main characteristics of this type of research is that the results can be depicted in numerical form.What is 5 important in quantitative research? ›
While there are a number of skills, techniques, and concepts you'll want to be familiar with, I think it's essential to master these five: reliability, validity, statistical significance, experimental validity, and correlations—the main factors that affect the quality of your findings.What are at least three examples of a quantitative research? ›
Quantitative data collection methods include various forms of surveys – online surveys, paper surveys, mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations.What are the 6 types of quantitative research? ›
- Descriptive Quantitative Design for Your Research. ...
- Correlational Quantitative Research Design. ...
- Quasi-Experimental Quantitative Research Design. ...
- Experimental Quantitative Research Design. ...
- (Causal) Comparative Research Design.
Quantitative data analysis involves the use of computational and statistical methods that focuses on the statistical, mathematical, or numerical analysis of datasets.What are 4 sources of research questions? ›
Research questions are developed by using sources that include curiosity, professors, textbooks, journals, databases, and the Internet.
Qualitative questions often produce rich data that can help researchers develop hypotheses for further quantitative study. For example: What are people's thoughts on the new library? How does it feel to be a first-generation student at our school?What are the most common research questions? ›
The most common starting questions are “what is your research about?" and “what was your motivation behind choosing this topic?” Later on, the committee asks you more detailed questions on research methodology, literature review, study variables, research findings, recommendations, and areas of further research. 6.What is an example of a research problem? ›
Examples of theoretical research problems include:
The relationship between genetics and mental issues in adulthood is not clearly understood. The effects of racial differences in long-term relationships are yet to be investigated in the modern dating scene.
Statistical analysis is the process of collecting and analyzing large volumes of data in order to identify trends and develop valuable insights. In the professional world, statistical analysts take raw data and find correlations between variables to reveal patterns and trends to relevant stakeholders.What is an example of a statistical data? ›
Amount of money, pulse rate, weight, number of people living in your town, and number of students who take statistics are examples of quantitative data.What is an example of data collection in quantitative research? ›
Quantitative research presents data in a numerical format, enabling researchers to evaluate and understand this data through statistical analysis. It answers questions such as “who?”, “when?” “what?”, and “where?”. Common examples include interviews, surveys, and case studies/document review.What is an example of quantitative analysis in education? ›
Types of quantitative data
Types of common quantitative data in schools might include: Student assessment scores and other student outcomes (for example reports found on Scout) Aggregates of responses from surveys (for example Tell Them From Me) Financial or Human Resources (HR) information.
- Mann-Whitney U test: equivalent to unpaired Students t-test.
- Wilcoxon rank sum test: equivalent to paired t-test.
- Wilcox signed rank test: equivalent to paired t-test.
- Kruskal-Wallis: equivalent to one-way ANOVA.
- Friedman's: equivalent to repeated measures ANOVA.
Some of the most common and convenient statistical tools to quantify such comparisons are the F-test, the t-tests, and regression analysis. Because the F-test and the t-tests are the most basic tests they will be discussed first.What is a simple quantitative analysis? ›
What is quantitative data analysis? Despite being a mouthful, quantitative data analysis simply means analysing data that is numbers-based – or data that can be easily “converted” into numbers without losing any meaning.
Quantitative analysis (QA) is a technique that uses mathematical and statistical modeling, measurement, and research to understand behavior. Quantitative analysts represent a given reality in terms of a numerical value.How many questions are needed for quantitative research? ›
A good questionnaire can be of 25 to 30 questions and should be able to be administered within 30 min to keep the interest and attention of the participants intact.What are the best quantitative interview questions? ›
- Why did you pursue a career in quantitative analysis? ...
- How much coding experience do you have? ...
- What is delta hedging? ...
- Tell me about a time you overcame an obstacle at work.
It looks like, on average, each resident of the city buys 1.6 pounds of candy per year. The mayor decides that this makes sense based on the facts of the problem, so he has his answer. The reasoning that the mayor used in this scenario is an example of using quantitative reasoning to solve a real-world problem.What type of questionnaire is used in quantitative research? ›
Close-ended questions are best used in quantitative research because they allow you to collect statistical information from respondents. If you want to gather a large amount of data that can be analyzed quickly, then asking close-ended questions is your best bet.What are the 7 characteristics of quantitative research? ›
- Contain Measurable Variables. ...
- Use Standardized Research Instruments. ...
- Assume a Normal Population Distribution. ...
- Present Data in Tables, Graphs, or Figures. ...
- Use Repeatable Method. ...
- Can Predict Outcomes. ...
- Use Measuring Devices.
Its main characteristics are:
The results are based on larger sample sizes that are representative of the population. The research study can usually be replicated or repeated, given its high reliability. Researcher has a clearly defined research question to which objective answers are sought.
For example, quantitative research is useful for answering questions such as: Is there a market for your products and services? How much market awareness is there of your product or service? How many people are interested in buying your product or service?What are research questions examples? ›
|Research Question Type||Question Formulation/Example|
|Correlational research question||What is the relationship between baldness and age?|
|Exploratory research question||Is it possible that VEGF has an effect in plant photosynthesis?|
|Explanatory research question||What is the cause of increased violence among young adults?|
Quantitative data is data that can be counted or measured in numerical values. The two main types of quantitative data are discrete data and continuous data. Height in feet, age in years, and weight in pounds are examples of quantitative data.
Multiple choice questions are a great quantitative survey question because they produce data that is easy to analyze. Similar to multiple choice, multiple answer, or check-all that apply, questions aim to be comprehensive.Which research question is best answered with a quantitative design? ›
Questions focused on the cause, prognosis (course), diagnosis, prevention, treatment, or economics of health problems are best answered using quantitative designs, whereas questions about the meaning or experience of illness are best answered using qualitative designs.Why are quantitative questions good? ›
Quantitative questions will result in data that is easy to convert into objective, numbers-based analysis. Quantitative data is easier to measure using statistical analysis, because you can (usually) assign numeric values and directly compare different answers to the same questions.What are the 7 basic questions in market research? ›
- Demographic questions e.g. How old are you? ...
- How likely are you to recommend us to a friend?
- Did you consider any of our competitors? ...
- What do you wish our product could do?
- How would you rate your most recent experience with us?
- How long have you been a customer?
Quantitative environmental science uses methods such as statistics, calculus and linear algebra to accrue and shape data. For example, a quantitative research project could seek to learn the number of North Americans who rely in part on wind, solar or nuclear energy to power their homes.