## ARTICLE 39: Research Methods for Ph. D. and Master’s Degree Studies: Statistical Research Methods Part 1 of 2.

Written by Dr Hannes Nel

Introduction

Technicist scientists are of the opinion that natural science is the most reliable path to the truth.

They, furthermore, claim that the truth can only be known through scientific proof.

Truth is based on logic, they say.

They believe in the singularity of meaning.

Something is either true or false – there is no in-between.

That is why they often base their research on hypotheses rather than a research question or statement.

They also believe that the truth can be proven and expressed numerically.

And they believe that the truth is not dependent on context or time.

Social scientists do not agree.

They feel that experience and reflection should not be neglected.

Individual and group perceptions can often be the truth.

The truth can be different in different contexts and at differ times.

Logic is simply common sense.

I will discuss the following issues related to statistical research methods in this article:

1. Investigating a statistical hypothesis.
2. Conducting statistical regression analysis.

Investigating a statistical hypothesis

You will mostly use a hypothesis in statistical research, although it is also possible to base your research on a problem statement or question.

You will need to formulate two opposing hypotheses – the null hypothesis and the alternative hypothesis.

The null hypothesis, indicated with H0, (H-naught) is a statement about the population that you believe to be true.

The alternative hypothesis, indicated with H1, is a claim about the population that is contradictory to H0. It is what we will conclude when you reject H0.

A null hypothesis can often be proved or disproved by means of statistical research.

One of your samples will support the H0 hypothesis while the other will support the H1 hypothesis.

You will reject the H0 hypothesis if the sample information favours the H1 hypothesis.

Or you will not reject the H0 hypothesis if the sample information is insufficient to reject it.

For example, your H0 hypothesis can be:

30% or less of the people who contracted the COVID-19 virus lived in rural areas.

You can also write the null hypothesis like this: H0 ≤ .3

Your H1 hypothesis will then be:

More than 30% of the people who contracted the COVID-19 virus did not live in rural areas.

You can also write the alternative hypothesis like this: N1 > .3

You will also need to calculate the size of the sample that you should use with a certain accuracy probability.

Dedicated computer programmes will do this for you.

Once you have composed a sample that will give you some answers with an acceptable level or probability, you will need to interpret the data that was probably analyzed with dedicated software.

You will need to set certain norms, or criteria, for the analysis of the data that you collected for the population first.

The samples also need to meet those norms, criteria or parameters.

A null hypothesis needs to be proven by comparing two sets of data.

If you reject the null hypothesis, then we can assume that there is enough evidence to support the alternative hypothesis.

That is: More than 30% of the people who contracted the COVID-19 virus did not live in rural areas.

You will probably compare the mean of observations or responses for the two sets of data.

It might sometimes be necessary to use the mode, median or correlation between the sets of data.

Random variability between different samples will also always be present.

There might also be small differences between the statistical relationship in the sample and the population.

It is possible that this can be just a matter of sample error.

Dedicated computer software will do the statistical calculations for you.

A null hypothesis does not “prove” anything to be true, but rather that the hypothesis is false.

If you cannot prove the two phenomena or populations to be different, then they are probably the same.

Then again, if the statistical analysis does not enable you to reject the null hypothesis, it does not necessarily mean that the null hypothesis is true.

Conducting statistical regression

Statistical regression analysis is a generic term for all methods in which quantitative data is collected and interpreted to numerically express the relationship between two groups of variables.

The expression may be used to describe the relationship between the two groups of variables.

It can also be used to predict values, although one must be careful of trying to predict future trends based on statistical data.

The two data groups, popularly represented by X and Y, are compared numerically or graphically to identify a relationship between the items or groups of items X and Y.

You can mostly use such comparisons to determine trends and correlation between variables.

It might, for example, be possible to identify a correlation between the hours that a student spends studying and his or her eventual performance in the exam.

Correlation measures the strength of association between two variables and the direction of the relationship.

In terms of the strength of the relationship, the values of the correlation coefficient will always vary between +1 and -1.

A value of +1 indicates a perfect degree of association between the two variables.

That means that if one thing happens, then something else will also happen.

For example, if you cut your arm you will bleed.

A value of -1 indicates a negative relationship between two variables.

For example, the faster you drive, the less time will it take you to reach your destination.

For example, the decrease in the number of new individuals that test positive for the COVID-19 virus does not enable us to predict when the pandemic will come to an end.

You can, perhaps, argue that correlation enables you to predict what will happen to one variable if a second variable changes.

However, predicting that such change will take place is often difficult, if not impossible in social sciences.

You can predict with a good measure of accuracy what will happen if you add certain amounts of yeast to the dough for baking bread.

But you cannot always predict how the baker will respond if she or he serves you the bread and you criticize it.

The situation is different in exact sciences, such as chemistry, where the scientist can initiate the change and control the size, measure and frequency of change.

Summary

You will probably use two opposing hypotheses in statistical research.

The null hypothesis is a statement about a population that you believe to be true.

The alternative hypothesis should contradict the null hypothesis.

You will use two samples to prove or disprove your hypothesis.

The findings that you gather from your analysis of the samples should apply to the population as well.

There might, however, be a sample error of which you should take note.

Statistical regression analysis investigates the relationship between two sets of variables.

It can show a correlation between the sets of variables.

It can also sometimes be used to predict values.

I would rather call it “foresee” values, because prediction based on statistics can be risky.

Relationships can be compared numerically or graphically.

Correlation between two variables can be anything between +1 and -1.

A value of +1 would indicate a perfectly positive correlation.

A value of -1 would indicate a perfectly negative correlation.

## ARTICLE 16: The Research Problem, Question or Hypothesis for a Ph. D. Dissertation or a Masters Degree thesis

Written by Dr. Hannes Nel

Introduction

Did you notice that some Ph. D. students formulate their research question, statement to impress rather than to explain?

A good research problem, question or hypothesis defines the focus of your research project.

The focus should, furthermore, be aimed at achieving the purpose of the research.

In the case of doctoral studies, the Postgraduate Committee will use the research problem, question or hypothesis to judge if your proposed research topic meets the requirements for research towards Ph. D.

You will need to narrow your research question, problem or hypothesis down to a project that you will be able to cope with, bearing in mind how much time and funds you have available for the research.

Keep in mind that research should always be the foundation for further research.

Let us refine and simplify an example of a research problem until we reach the point where it meets the requirements for viable research on the doctoral level.

1. What is the effect of global warming on social interaction?

A research question like this creates more questions than it solves.

• It is vague and the effect of global warming on social interaction can be a multitude of possible things, for example, relationships in the classroom, at home, between married couples, between friends, clients versus salespeople, etc.
• The effect of global warming on different continents, in different countries, different cultures, different seasons, etc. will probably not be the same.

You will need to explain and define the research question. However, even then it would be almost impossible to conclude generally applicable findings that will apply to the entire world and all people and times of the year.

Here is a second refinement of the research question:

• What is the effect of global warming on the social interaction of people to work in metropolitan areas?

This research question already hints on possible economic value. It is limited to a specific type of living area and it would probably be possible to choose a representative sample for the research.

You should be careful of not formulating your research question in such a way that it renders your research subjective and biased.

For example, if you were to ask “Will global warming cause people working in metropolitan areas to lose interest in social interaction?” you might create the impression that you are of the opinion that global warming will cause people who work in metropolitan areas to lose interest in social interaction.

It might still be a workable problem to investigate, though. You can also reformulate your problem statement or question as a hypothesis, especially as the answer to your question might simply be “yes” or “no”. You might even be able to statistically prove your hypothesis as valid or not. Here you would probably use quantitative research and a technicist paradigmatic approach.

A hypothesis will be formulated somewhat differently from a research question or problem statement.

I will discuss more intricate examples of hypotheses in the videos on quantitative research methods.

You can avoid the dichotomous nature of this last example (the answer can only be “yes” or “no”) by formulating it something like this:

“What is the impact of global warming on the social interaction between people working in metropolitan areas?”

Regardless of how you formulate your research problem, question or hypothesis, you will still need to describe the context for your research.

The purpose of your research can also help to clarify your research question, problem or hypothesis.

The scope of your research can help you to know where to go, what to investigate and when to stop with your research.

Your research question, problem or hypothesis is not final if you did not submit your final dissertation or thesis yet.

However, keep in mind that it will become increasingly more difficult and riskier to change your research question, problem or hypothesis the longer you wait to do so.

Summary

A research question, statement or hypothesis gives you a good indication of which data you need to collect and which methods you will use to access and analyze your sources.

You need to explain the focus, purpose, scope and motivation for your research.

You also need to motivate your research question, problem or hypothesis clearly and objectively.

The rationale for your research question, statement or hypothesis can serve of evidence that your research project is viable.

You can change your research question, statement or hypothesis any time while you are still doing research. However, the longer you wait, the more incorrect data will you collect, and the more time will you waste on doing unnecessary work.

## ARTICLE 15: Creating a Draft for a Ph.D. Dissertation or a Masters Degree Thesis

Written by Dr. Hannes Nel

Introduction

In my previous article, I discussed writing a second chapter for your Ph. D. dissertation or master’s degree thesis.

It might sometimes be necessary to break the second chapter down into two or three chapters.

You will write many different versions for a draft thesis or dissertation, and you will continue reviewing what was probably just a structure in the beginning until you reach the point where you will have a final product.

The following seven steps will enable you to write a first draft.

The outline should be an abbreviated picture of the parts of your dissertation or thesis.

You can use the outline as the scope of your dissertation, or perhaps your thesis if and when you need to defend your final submission.

The outline can help you prevent and identify flaws in the structure of the dissertation or thesis.

Step 2: Check your research statement, question or hypothesis

You will have written your research statement, question or hypothesis when you prepared your research proposal.

You can refocus the research statement, question or hypothesis at any point while writing your thesis or dissertation, if necessary.

You can also refocus it as often as you wish, although you should not do this indiscriminately.

Refocusing your research problem, question or hypothesis would be necessary if you were too ambitious when you decided on the scope for your research.

You will need to refocus your research problem, question or hypothesis if you run out of time.

However, your study leader will not take kindly to you running out of time if you dragged your feet.

Step 3: Write the body of your dissertation or thesis from your notes

This is where you will ensure that what you write flows logically.

You should check if all your ideas, arguments, evidence, figures and tables flow logically, much like the narrative for a novel.

In the old days, we used notecards for this.

Now we have computers that make the work much easier.

Step 4: Check that you cite all the information that you quoted from other sources with parenthetical citations

Parenthetical citations are where you recognize the authors of the text, statistics, etc. that you use in your dissertation or thesis.

You must cite your sources when using the following kinds of material, in whole or in part:

1. Direct quotations.
2. Paraphrased and reconstructed quotations. (Quotations of which you changed the original wording somewhat.)
3. Statistical data.
4. Images made by someone else.
5. Song lyrics.
6. Original ideas that belong to someone else.

I will discuss referencing methods in a future article.

The introduction normally has two parts:

1. A general introduction to the topic of your research.

You will write your conclusions after you have done the literature study and fieldwork.

Through the conclusions you should show:

1. The reader that the work is complete and well done.
2. That the research project has been brought to a logical and realistic end.
3. That you have made a positive contribution to the field of your study.

You can restate your research problem, question or hypothesis here.

You can also summarize your main points of evidence here.

Step 7: Create a title page

You can prepare the title page at any stage while doing your research and writing your report.

Here you must prepare the title page according to the format and requirements of the university or faculty where you study.

Reviewing your draft dissertation or thesis

You can and probably will submit chapters or perhaps just sections that your study leader would like to see from time to time.

However, do not submit what you might regard as a final product unless you feel proud of the work that you did.

You should feel confident that your study leader will be satisfied with your work, so much so that you are looking forward to his or her feedback.

And even though you might expect to be showered with praise, you need to realize that the opposite might still happen. Be prepared for what you might regard as cruel, unfair and unnecessary criticism.

This is when you will need to show character. Now is the time when you will need to show that you can persevere.

Do not blame your study leader for not being as impressed with your work as you are. Listen, or read, the feedback carefully and give yourself time to think about it, to absorb it and to decide how you can benefit from the disappointment.

You can and should pre-empt negative feedback by evaluating and correcting your work even before your study leader tells you to do so.

Here are nine questions that you can ask of your work to find opportunities for improvement:

1. Is it necessary to introduce new material, data, ideas and thinking? If yes, then find the additional content and include it.
2. Did you include arguments or information in your dissertation or thesis that adds no value because it is not relevant to the purpose of your research? If so, remove such padding from your report.
3. Is there data or arguments that you included early in your report that later proved to be outdated or irrelevant?
4. Is there more recent and relevant data or arguments in a later chapter or chapters? Remove obsolete data and arguments.
5. Can you find any cognitive mistakes in any of your arguments, conclusions, assumptions or recommendations? If so, remove the errors or correct them.
6. Is the structure of your chapters or sections in chapters erratic? Good software, such as ATLAS.Ti can often solve the problem. Sometimes logical thinking can also do wonders for the flow of your report.
7. Did you respond negatively, aggressively or immaturely to feedback from your study leader, assistant study leader or perhaps even one or more external examiners? Apologize and thank them for their assistance. Correct your errors and inform them how you used their feedback to improve your work.
8. Did you repeat theoretical data, arguments, etc. in your dissertation or thesis? Even simple office software, like Microsoft Word, can find the repetition of sentences if you suspect that you repeated a statement and “ask” the software to find it.
9. Did you, at any stage while writing your dissertation or thesis, use a research method or paradigm incorrectly? It can happen that you “drifted” from one research method or paradigm to different, more suitable ones. This is not always wrong, but if the research methods or paradigmatic approaches contradict one another you will need to correct the error.

Probably all research topics on the doctoral level are of such a nature that the perfectionist will never be satisfied with the report. There will always be something that needs improvement.

You must draw the line somewhere, even if the temptation to just do this and that more might be strong.

Summary

You can use the seven steps that I discussed to prepare your first draft.

You will end up writing and saving many versions of your dissertation or thesis until you reach the point where you are satisfied that you have achieved the purpose of your research project.

You can and should review and improve your draft report intuitively by correcting flaws when you identify them.