What are the main types of quantitative / approaches to research
What are the main types of quantitative
The question is somewhat unclear: “What are the kinds of quantitative research?”
I think we could simplify it as quantitative research, as opposed to qualitative research, is about counting things, rather than describing them.
We can usually do this through administrative data (how many people in the population meet criteria x) or most commonly, using a survey (on a scale of 1–5, how do you rate x).
We don’t know why something happens, but we do know how much of it is happening by counting the effect using quantitative analysis.
Here are some examples of quantitative research titles:
- An investigation to establish the average length of Quora questions
- An investigation into the average height of human beings worldwide
- A study of the changing world temperature
- Comparing paint thicknesses in various kinds of paints
All of these studies can be expressed in numbers, perhaps using tables and statistics. hence they are quantitative.
4 types of quantitative research in 2020
There are four main types of quantitative research designs: descriptive, correlational, quasi-experimental and experimental.
The differences between the four types primarily relate to the degree the researcher designs for control of the variables in the experiment.
Following is a brief description of each type of quantitative research design, as well as chart comparing and contrasting the approaches.
1 Descriptive Design
A Descriptive Design seeks to describe the current status of a variable or phenomenon.
The researcher does not begin with a hypothesis but typically develops one after the data is collected.
Data collection is mostly observational in nature.
2 Correlational Design
Correlational Design explores the relationship between variables using statistical analyses.
However, it does not look for cause and effect and therefore, is also mostly observational in terms of data collection.
3. Quasi-Experimental Design
A Quasi-Experimental Design (often referred to as Causal-Comparative) seeks to establish a cause-effect relationship between two or more variables.
The researcher does not assign groups and does not manipulate the independent variable.
Control groups are identified and exposed to the variable.
Results are compared with results from groups not exposed to the variable.
4. Experimental Designs
Experimental Designs often called true experimentation, use the scientific method to establish cause-effect relationships among a group of variables in a research study.
Researchers make an effort to control for all variables except the one being manipulated (the independent variable).
The effects of the independent variable on the dependent variable are collected and analyzed for a relationship.
Kinds of quantitative research
Quantitative research uses data (quanta) collected according to materials science research methods, also known as empirical studies.
These methods are suitable only for the “objective” phenomena found in physics, chemistry, biology, and not for “subjective” phenomena found in psychology, political science, sociology, etc.
Keep in mind that research can be data-driven, theory-driven or even math based on which, first of all, the theory needs data to confirm it, data to explain it Is required, or mathematics probably requires nothing but mathematics.
Ultimately quantitative research is dialectical between different sources, leads to data theory that leads to more data, etc.
As far as my ‘hobby’ of exorcism is concerned, negative thought-forms (demons) aren’t that easy to analyze.
Their main ‘aim’ is to catch your attention by asserting something about your private life history through the possessed person that the possessed person has never met you before and has no way of knowing what they say happened – this is to pull your attention energy into their parasitic mentality – to sabotage your focus in expelling them.
To reach such a point in practice, a fair few years of analysis of overall aspects of demonic possession could, I suppose, loosely be called ‘quantitative research’.
Though the number of illogical aspects of that subject is considerable. I daresay other answers may be of more use to you.
As far as demonic thought-forms are concerned – the one thing they hate – simply because it can never be destroyed – is All Truth.
What are the characteristics, strengths, weaknesses, and kinds of quantitative research?
Quick and dirty (very much so)
Multiple data points, lots of math (calculus) and numbers, outliers that skew the results, standard deviations, normal regression, logit regression, Poisson regression, sampling errors, correlation != causation, ghosts in the machine (STATA errors that make no sense), non-convergence for sometimes hours until you get the variables right (grrr), ….
And that’s just off the top of my head from what I remember of methodology classes 10 years ago.
Here is Some Explain
Quantitative research covers a wide variety of techniques.
In the most common approach, quant is a systematic implementation of fundamental ideas. Ex:
- A multifactor value model sounds complicated but probably has a lot in common with simple Value Investing ideas (P/B, P/E) that date to Benjamin Graham.
- Quality of Earnings work is based on a paper by Richard Sloane. The idea is that examining cash flow and accruals can provide insight into where accounting is aggressive/conservative, and whether earnings are sustainable.
- Earnings Surprise and Estimate Revision use the simple notion that positive surprises tend to be followed by more positives, and negatives by more negatives.
The biggest advantages of quant are:
- Systematic. The approach is applied consistently, whereas comparing the work of different fundamental analysts is problematic.
- Breadth and cost. Quant models can examine a vast quantity of stocks quickly. Fundamental analysis of a large number of stocks would require a herd of expensive analysts.
I believe that the best quant investing includes some fundamental work, not just verifying model inputs, but looking for details that models cannot cover. Ex:
- Lawsuits. You find a chemical company that looks very cheap, but it has polluted an entire town in litigation-friendly Alabama. This is a real-life example (Solutia) from the last decade.
- Customer concentration. If a firm has one very large customer and loses that customer, that’s not good for the stock. See TESS a few years back.
types of quantitative research
Quantitative research relies on connecting the empirical observations with mathematical representation, i.e. it relies on measuring a set of data.
Like any other research, this requires careful planning and execution, which can have various loopholes.
I will tell you the setbacks I face while doing quantitative research:
- Time-consuming: I work with cells and my experiments involve quantifying the localization of different proteins under different conditions. I usually count 1000–1500 cells per condition; most of which are manual.
- Inability to control the microenvironment: Biology, as a subject, is quite messy and unpredictable. Unlike physics or chemistry, every reaction or problem can have various outputs, some of which we don’t even consider. For example- the cells I work with are quite finicky, they lose their ability to undergo differentiation if they grow too close to each other in the growth medium. At times, it is difficult to control them because they grow at a crazy rate thereby affecting my results.
- Difficulty in data analysis: Despite having quite a number of software for image analyses, often it is difficult to measure certain features because the method doesn’t give out or represent the information of the image. It requires more clarity and perhaps a more refined way like a different code. Figuring that out takes time and might not be doable under certain conditions.
These are pretty much the 3 things that I think are the weaknesses of quantitative research.
Other weaknesses (which I have not encountered yet) might include:
- Variability- applicable for manual quantification
- Inappropriate representation of sample sets
- Lack of resources
Hope this answers your question. Cheers. 🙂
types of quantitative research
4 types of quantitative research