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Ethics

“Derived from the Greek ethos, meaning character, custom, or usage, or morality (from the Latin synonym meaning manner, custom or habit)

“Research ethics resolves practical problems in the conduct of research.

Ethics are moral principles and values that guide human behavior and decision-making, shaping how we treat ourselves, others, and the world around us.

Ethics can apply to various aspects of life, such as:

-Medical ethics (e.g., patient confidentiality)

– Business ethics (e.g., fair trade practices)

– Environmental ethics (e.g., sustainability)

– Personal ethics (e.g., honesty, integrity)

-Professional ethics (e.g., codes of conduct)

Ethics & Success

Unethical behavior (Incorrect or unacceptable) / Social behavior shapes some of our ethical standards.

Ethics and Success :

“Ethics are not a choice, but a foundation that success might overlook or compromise.” Or, in even simpler terms: “Success can sometimes lead to neglecting ethical principles.

 What might lead to unethical behavior? 

1.  Ignorance

Why some professors/seniors don’t teach ethics??

They are not aware or well-qualified

By the time students go to college their character is already shaped

High expectations:

-We teach Mathematics but don’t’ expect students to be   Mathematicians.

-We teach ethics to inform and not to make students ethicists

Examples

Students don’t understand how to cite references properly
and that leads them to plagiarize.

Teachers don’t gossip and obey the rules.

Running an experiment and using 96% of results. What do we do with the remaining 4%

How much work must be quoted without citation to plagiarize?

Forgot to include a source or simply negligence.

Ignorance leading to unethical behavior

Policies and standards of the University or the institution should be taught to the students.

Make sure that policies and standards are followed properly

•Before it used to be monitoring, but now it is not enough since labs are growing and more money and deadlines are involved

Telling students where to go with ethical concerns and which dean/faculty to talk to if he needs that.

2. Stress

I must get this grant

I need to get published

I must meet this deadline

Getting some thing done might seem more important than how to get it done.

We cannot remove stress but we can teach people how to deal with it.

Talk about the outcome of forging data and future consequences

  Forging data is the same as data fabrication and is related to data falsification.

Patience and immediate result problem

Teach students to talk to teachers:

Protest the load of work

Designed experiment is not working and that is leading to this data. Change the design.

Ask for help when they need it and help them when they ask.

When things are not clear any more, step back and think objectively.

Reduce the load of work

Always think that there is an acceptable and ethical outcome

Teach students to think under stress

Who will blow the whistle?

What to do when you see some one behaving unethically?

Relationship with that person will change the way you deal with the situation

A fellow faculty or a competitor.

Students make mistakes, you need to tell them that it is wrong to do it that way and direct them to the right way

Witnessing misconduct

Make sure that there is abuse by documenting misconduct and try to get witnesses and facts

Prepare a solid foundation

Approaching the situation the right way

Can you explain those anomalies to me?   OR   How long have you been forging data?

If the person denies misconduct you need to go to higher level.

Students must be taught to:

Blow the whistle and report misconduct

Which dean/faculty to talk to?

What are the policies and regulations?

What is an approved procedure for reporting misconduct?

Concepts of Ethics

Moral Sensitivity:

“ The ability to recognize an issue or a problem as a moral problem”

 (Penslar,1995 ).

Identifying actions or ranges of actions that might define some actions that are ethical and some actions that are unethical like the use of animals in research.

Moral reasoning:

“Is the process of thinking about proper course of action when faced with an ethical challenge” (Penslar, 1995 ).

Not different from scientific reasoning but practice is a good idea.

Moral commitment:

“Is what takes to choose a ethically sound course of action over an unethical course of action” (Penslar, 1995 ).

What is the primary commitment

Ethics

Wealth

Successful research

Good research and Ethical Research

Drawing the line between good research and ethical research is not always clear.

“Good research is concerned with the integrity and the soundness of data, where as research ethics is concerned with the means the data was collected” (Penslar, 1995 ).

Research ethics is concerned with the well-being of others( Society, other people, animals) while Good research does not necessarily do that.

Issues in research ethics:

Conduct of individuals

Research fraud

Mistreatment of lab animals

Accuracy and honesty in reporting results

Plagiarism

Violation of intellectual property rights

Conflict of interests ( researchers among each other or researchers and universities)

Check if a research is harmful to the society or to individuals. How universities should resolve their conflicts among them selves.

Ethical research

Helpful resources:

Professional codes

Statement of moral norms by members of a profession

Government regulations

More like laws

Use of humans as subjects of experiments

Religion

Cultural customs

Ethical theories:

Consequential ethics

Mandatory ethics

Casuistical ethics

Virtue ethics

Consequentialist Ethics

What are the possible harms that might result of an erroneous publication?

What response from me knowing that the results are wrong will result in more harm than good?

What harm might be done if the research results are not corrected?

What harm might I cause that person if I bring the subject out?

What are the benefits of talking to that person first?

What if that person used my approach to cover his/her track.

How each action will affect that person if he is innocent?

Mandatory Ethics

What is my duty if I discover errors in some research?

What is the right thing to do in this case?

Were those errors caused deliberately or negligently?

If negligently, what is the best way to reverse the effect of the misinterpreted information?

If deliberately then I must report this situation or get an investigation started.

Some acts are right or wrong regardless of the consequences

We decide if an act is right or wrong by following rules that are supported or justified by principles.

Example:

“Don’t deliberately distort your data by eliminating outliers” is a rule, but truthfulness is a principle.

Casuistical (misleading) Ethics

Is this a case of intentional wrong doing, where the researcher deliberately published false information for personal gain?

This is clearly unethical

Is this a case of negligent oversight, where the researcher did not the check the results before submitting them to publication?

You may need to find more information about the motives before making any decision.

Virtue Ethics

What is the person’s moral character?

Is this the first time that this happens with this person?

How likely is he to deal with this issue honestly?

Is he going to take use of my good will approach to uncover the errors?

Would uncovering the errors damage his reputation and character as a researcher?

What are my motives behind uncovering those errors?

Do I hold a grudge against this person and I want to see him suffer even if his mistakes were not intentional?

Basic ethical principles

Respect for persons:

The person should be treated as autonomous.

The person with diminished autonomy is entitled to protection.

(controlled by others or incapable of deliberating or acting on the basis of his or her desires and plans.)

Who is an autonomous person:

Can think and discuss his personal goals and act under those goals.

Protect those who cannot make their own self-determination or are not eligible for doing so.

Beneficence:

Not only respect their decisions and protect them from harm but also make an effort to secure their well being.

Think of this as an obligation and not a charity.

Do not harm,  and maximize possible benefits and minimize possible harms.

Justice:

The right to be treated equally.

Some one is denied benefits for no obvious reason.

The principle of fairness in distribution.

Also read: DATA Collection And DATA Analysis Methods Lecture By Dr. Ghazala Ali Khan

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What is Data?

Collection of facts, figures, and statistics that are used to inform, analyze, and make decisions is called Data.

Types of Data:

It can be in the form of numbers, words, images, sounds, or videos.

Data can be quantitative (numerical) or qualitative (non-numerical).

Examples of data include: –

Numbers: sales figures, temperatures, stock   prices

Text: customer feedback, social media posts, survey responses

Images: photos, videos, medical scans

Audio: voice recordings, podcasts

Other: sensor/ satellite readings, GPS locations, website traffic

Data can be used to: –

-Identify patterns and trends

-Make predictions and forecasts

-Inform business decisions

-Evaluate performance and progress

Answer questions and solve problems In today’s digital age, data is generated and collected at an unprecedented scale, and its effective use has become a key driver of innovation, competitiveness, and success in various fields.

Scientific Data

Scientifically, data refers to a collection of quantitative (numerical) or qualitative (non-numerical) values that are obtained through observation, measurement, or experimentation.

These values are typically numerical or categorical in nature and are used to describe phenomena, patterns, or relationships.

In a scientific context, data is usually considered to be:

1.Empirical:

Data is based on observation or measurement, rather than on intuition or assumption.

2.Systematic:

Data is collected in a structured and organized way, using a predetermined methodology.

3.Quantifiable:

Data can be represented by numbers or categories, allowing for statistical analysis and mathematical manipulation.

Important to Remember:

Data is intended to be free from personal biases and subjective interpretations.

Verifiable:

Data can be checked and validated through repetition or cross-validation.

Examples of scientific data include:

Sensor readings from a laboratory instrument

Survey responses from a population sample

Gene expression levels from a biological experiment

Climate patterns from satellite imagery

Data Analysis and Interpretation

Major Steps for Data analysis:

Involves three major steps,

1.Cleaning and organizing the data for analysis (Data Preparation / Compilling)

2.Describing the data

3.Testing Hypotheses and Models

Statistics

A set of mathematical procedures for describing, synthesizing, analyzing, and interpreting quantitative data.

The selection of an appropriate statistical technique is determined by the research design, Hypothesis, and the data collected.

Compiling Data for Analysis

Data must be accurately recorded and systematically organized to facilitate data analysis:

Tabulating: organizing the data in a systematic manner

Coding: assigning numerals (e.g., ID) to data

Important To Remember:

Data analysis is the process of finding the right data to answer your question,

Understanding the processes underlying the data,

Discovering the important patterns in the data,

and then communicating your results to have the biggest possible impact

Parameters

indices (keywords/hints) calculated by the researcher for an entire population

Statistics

indices calculated by the researcher for a sample drawn from a population

Descriptive statistics

permit the researcher to describe many pieces of data with a few indices (tables/graphs/etc, T-test, T-test)

Types of descriptive statistics

1. Graphs

representations of data enabling the researcher to see what the distribution of scores look like

2. Measures of central tendency

indices enabling the researcher to determine the typical or average score of a group of scores

3. Measures of variability

Mode / Median, Mean

Mode – the  value that occurs the most times

Median – the middle of the distribution, the number where half of the values are above and half are below

 Mean – average of all values of this variable in the data set

Range of values – from minimum value to maximum value

Data Analysis Procedure

Coding – process of translating information gathered from questionnaires or other sources into something that can be analyzed

Involves assigning a value to the information given—often value is given a label

Coding can make data more consistent:

Example: Question = Sex

Answers = Male, Female, M, or F

Coding will avoid such inconsistencies

Coding Systems

Common coding systems (code and label) for dichotomous variables:

             0=No  1=Yes  

  (1 = value assigned, Yes= label of value)

OR:  1=No  2=Yes

When you assign a value you must also make it clear what that value means

In first example above, 1=Yes but in second example 1=No

As long as it is clear how the data are coded, either is fine

You can make it clear by creating a data dictionary to accompany the dataset

Few frequently used Software for Data Analysis

Statistics 8.1

State X

SPSS

R

MS Excel

Also read: Sampling and Sampling Methods By Dr. Ghazala Ali Khan

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Sampling

PPS (Probability Proportional to Size) Sampling

Is a sampling technique in which the selection of units is proportional to their size (experimental Population).

Where the size of a unit is typically measured by a characteristic such as population, revenue, or number of employees.

Scientific sampling

Also known as probability sampling, is a research methodology used to select a representative subset (sample) from a larger population.

This approach ensures that the sample is representative of the population.

Allowing researchers to generalize their findings to the larger group.

The key characteristics of scientific sampling

1.Random selection:

Participants are chosen randomly from the population, reducing bias and ensuring that each individual has an equal chance of being selected.

2.Representative:

The sample is representative of the population in terms of relevant characteristics, such as demographics, behaviors, attributes , characteristics, qualities, or traits.

3.Probability:

Each member of the population has a known probability of being selected, allowing researchers to calculate the margin of error and confidence intervals.

Probability is a measure of the likelihood of an event occurring.

Probability theory is a branch of mathematics that deals with the study of chance events and their probabilities. It has numerous applications in fields such as statistics, engineering, economics, and finance.

What is Probability:

It is a number between 0 and 1 that represents the chance or probability of an event happening.

-0 represents an impossible event

-1 represents a certain event

– A value close to 0 represents an unlikely event

-A value close to 1 represents a likely event

-Probability is often expressed as a percentage or a fraction, and it is used to quantify uncertainty and make predictions about future events.

We have a bag of 5 red marbles and 3 blue marbles.

Question:

What is the probability of drawing a red marble from the bag?

Answer: There are a total of 8 marbles (5 red + 3 blue).

The number of favorable outcomes (drawing a red marble) is 5. So, the probability is:

Probability = Number of favorable outcomes / Total number of outcomes = 5/8 = 0.625

This means that the probability of drawing a red marble is 0.625 or 62.5%.

In simple terms, if you draw a marble from the bag many times, you would expect to get a red marble about 62.5% of the time.

4.Systematic:

The sampling process is systematic, using a predetermined procedure to select participants, such as random number generators or stratified sampling techniques.

Stratified Sampling:

This sampling allows researchers to divide particular populations into subgroups called Strata

Example:

Institute….. 03-Subjects…. Take sample from each subject… for analysis

Common types of scientific sampling include:

1.  Simple Random Sampling: Each member of the   population has an equal chance of being selected.

2. Stratified Sampling: The population is divided into   subgroups, and a random sample is selected from   each subgroup.

3. Systematic Sampling: Every nth member of the   population is selected, where n is a fixed number.

4. Cluster Sampling: A random sample of groups (clusters)   is selected, and all members of each cluster are   included in the sample.

Importance of Scientific sampling

Scientific sampling is essential in research, as it allows researchers to:

1.Generalize findings: Results can be applied to the larger population with a known degree of accuracy.

2.Minimize bias: Random selection reduces the influence of personal biases and ensures a representative sample.

3.Increase efficiency: Sampling is often more feasible and cost-effective than studying the entire population.

4.By using scientific sampling, researchers can ensure that their findings are reliable, valid, and applicable to the larger population.

Factors that influence sample representative-ness

3 factors that influence sample representative-  ness

•Sampling procedure

•Sample size

•Participation (response)

When might you sample the entire population?

•When your population is very small

•When you have extensive resources

•When you don’t expect a very high response

SAMPLING BREAKDOWN

Process

•The sampling process comprises several stages:

–Defining the population of concern

–Specifying a Sampling Frame, a setof items or  events possible to measure

–Specifying a sampling method for selecting  items or events from the frame

–Determining the sample size

–Implementing the sampling plan

–Sampling and data collecting

–Reviewing the sampling process

Population definition

•A population can be defined as including all  people or items with the characteristic one  wishes to understand.

•  Because there is very rarely enough time or  money to gather information from everyone  or everything in a population, the goal  becomes finding a representative sample (or  subset) of that population.

•Note also that the population from which the  sample is drawn may not be the same as the  population about which we actually want  information. Often there is large but not  complete overlap between these two groups  due to frame issues etc .

•Sometimes they may be entirely separate –  for instance, we might study rats in order to  get a better understanding of human health,  or we might study records from people born  in 2008 in order to make predictions about  people born in 2009.

SAMPLING FRAME

•In the most straightforward case, such as the  sentencing of a batch of material from production  (acceptance sampling by lots), it is possible to  identify and measure every single item in the  population and to include any one of them in our  sample. However, in the more general case this is not  possible.

•There is no way to identify all rats in the  set of all rats.

•Where voting is not compulsory,  there is no way to identify which people will actually  vote at a forthcoming election (in advance of the  election)

•As a remedy, we seek a sampling frame which has  the property that we can identify every single  element and include any in our sample .

•The sampling frame must be representative of the  population

Also read: Literature Review Lecture By Dr. Ghazala Ali Khan

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What is Literature?

It refers to written works of art that explore the human experience, imagination, and intellect, often with aesthetic/visual and creative/experimental expression.

Areas Covered by Literature?

It covers various forms, such as poetry, drama, fiction, and non-fiction, that entertain, educate, and inspire readers, offering insights into the human condition and the world around us.

What is Scientific Literature?

Scientific literature is the principal medium for communicating the results of scientific research and represents the permanent record of the collective achievements of the scientific community over time.

Main Categories of Scientific Literature?

Primary literature:-

includes research articles, conference proceedings, patents, and dissertations, which are the original research findings.

Interview transcripts

Works of art or literature

Historical documents

Statistical data

Secondary literature:-

includes review articles/Journal articales, monographs, and textbooks/Scholarly books and Reviews.

(summarize and synthesize the primary literature)

Monographs**

monograph is defined as a highly detailed and thoroughly documented study or paper written about a limited area of a subject or field of inquiry

Primary vs Secondary Sources

Primary sources provide direct first-hand evidence

Secondary sources provide commentary or analysis

Examples:

The Cambridge Companion to the Victorian Novel

Jannat Kay Pattay, by Nemrah Ahmed

“Raja Gidh”, by Bano Qudsia

●A journal article about 19th-century literature

Primary or secondary?

Primary sources:

“Jannat Kay Pattay”, by Nemrah Ahmed

“Raja Gidh”, by Bano Qudsia

Secondary sources:

The Cambridge Companion to the Victorian Novel

A journal article about 19th-century literature

Few key points about scientific literature include:

Peer-reviewed articles are considered more reliable and of higher quality.

Scholarly articles are concerned with academic study, especially research.

Journal articles are the most widely used primary sources in the sciences.

peer review article is a scientific paper that has been reviewed by experts in the same field before publication. This process helps ensure the article meets high standards of quality, validity, and relevance.

Where is scientific literature published?

Scientific literature is published in various formats, including journals, magazines, series, and books.

Importance of Scientific Literature?

It is essential for research students and scientists to conduct and communicate their research

So From Where we Take Start

Start exploring the literature on your topic

Use books, journals, and other reliable sources

Consider a variety of perspectives

Use your reading to inform your arguments

Keep notes of source details and useful quotations

Very important to Keep In Mind Before Writing

Evaluating credibility: the CRAAP Test

Currency: Is the information up to date?

Relevance: Is it relevant to your research?

Authority: Where is it published and who is the author?

Accuracy: Where does the information come from? Is evidence provided?

Purpose: Why was this information published?

Outlining your structure:

Organize your thoughts

Understand the flow of information and how ideas are related

Ensure nothing is forgotten

Importance of Key Words in Scientific Literature Review:

1. Facilitate discovery: help readers find relevant articles and research papers.

2. Improve searchability: Keywords enhance the visibility of articles in databases and search engines.

3. Clarify content: Keywords provide a concise summary of the article’s topic and focus.

4. Enhance organization: Keywords help categorize and group similar articles together.

5. Support indexing and abstracting: Keywords aid in the creation of indexes and abstracts.

6. Facilitate meta-analysis: Keywords enable researchers to identify and synthesize relevant studies.

7. Increase precision: help researchers target specific topics and avoid irrelevant results.

8. Enable replication: Keywords facilitate the identification of similar studies for replication and verification.

By carefully selecting and using relevant keywords, authors can ensure their research reaches the intended audience and contributes to the scientific community’s collective knowledge.

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What is Research?

Research is a process in looking at solution of a given problem which can be used basis for:

•Knowledge improvement/enhancement

•Create new Knowledge

The Central or main Idea of Research!

A long piece of writing based on your ideas & research that you did as a part of your degree.

It’s a position you are arguing.

To Tell the reader what your research is about and use my work as guide for future research.

But before One come to the Solution:

•It should be backup with Observed /experimental Data which requires the proper process of research

Where does a thesis start?

Brain storming,

Reading

Reading &

Reading

Be more specific as u start

Formal Research

•To get a degree (BS/M.Sc., MS/M.Phil, Ph.D)

•In the form of a report/thesis

•The data/statements presented are original

•Avoid maximum plagiarism

So, where to begin & How long should a thesis statement be?

•One sentence

•Begin with Question— the question you are answering with your writing e.g.

what does hot weather play role in agriculture & why it is important?

•For this scholars have to reach books, articles & general reading

•Here Hot weather & Agriculture are symbols or key words

Revise your question based on your reading

what does hot weather play a role in agriculture outcomes & why it is important?

•Before finalizing the statement be assure your self that what u have selected as question, can U be able to justify with your literature in all clear possible ways.

•And be my reader get all the answers in his mind in a clear way.

•If you are not convinced then revise your statement again.

Be clear to answer the questions in statement, support answer with focus examples, with in a creative & thoughtful way.

Formal Research Format

Title of the study question

(somehow reflect objective, study area/population, and location)

Introduction/background and review of literature

•It should be not more than 10 to 15 pages

•Reflecting the background and depth of the problem in global, regional, and local contests with logical reasoning and references must be cited as per the recommended style by the Institute/university

Objectives /Hypothesis

Specific statements that reflect what actually you want to find out from the study

Methodology

Study Design, duration, Sample size, Sampling techniques, operation definition,  data collection and evaluation/analysis process and plan/techniques

Data Collection

Questioner, Sampling, audio/video tools etc.

So Systematic Process is a set of:

●procedures/methodologies/steps (that are developed after decades of research) are followed to achieve the objectives.

●These are considered valuable because they are free from any biases and subjectivity. And we can draw results/conclusions by following these.

What is Research Design?

Research design refers to the overall plan and structure of a research study, including the methods and procedures used to collect and analyze data.

It involves several key elements, such as:

1.Research questions or hypotheses

(Extraction of Essential Oil from different Varieties of Miaz / wheat

Fatty acids profiling)

2.Selection of Topic (Fatty Acid Profilling of Maiz/wheat etc)

3.Study type (e.g., experimental, survey, case study)

4.Data collection methods (e.g., experimental, interviews, questionnaires, observations)

5. Sampling strategy (e.g., random, snowball, stratified)

Snowball:

When Potential Participants are hard to find and start with 1 subject who provides 01 referral and so on) or

1^st subject recruited to the sample group and provide multiple referrals

Subjects give multiple referrals but only 01 recruited among them

Examples:

Homeless People / Criminal

Use of Medicinal Plants, to cure diseases

Data of Local healers / practitioners and their recipes

Stratified Sampling:

This sampling allows researchers to divide particular populations into subgroups called Strata

Example:

Institute….. 03-Subjects…. Take sample from each subject… for analysis

6.  Data analysis techniques (e.g., statistical (SPSS/ Statistics 8.1), qualitative (comparison of two or more selected subjects l)

7.  Research ethics considerations A well-crafted research design helps ensure that the study is conducted in a logical, systematic, and unbiased manner, and that the results are valid and reliable.

Types of Research Design

There are several types of research designs, including:

1.  Experimental Design:

 Involves manipulating one or more variables and measuring their effect on a dependent variable.

2. Case Study Design:

In-depth examination of a single case or a small number of cases.

Three basic reasons to choose Case Study Design;

1.When you have to answer why and how

2.When not able to manipulate variable and individual behaviors

3.Want to explore a particular Situation & in-depth finding

Example:

How Moral Education Affects Students Attitudes

How Slang Words Effect Society and Langue

3. Survey Research Design:

Involves collecting data through self-report measures such as questionnaires or interviews.

Its non-experimental Research

Or a part of experimental research

Example:

Collect info from a group of population with different Subjects (Hospital, Cancer, Types of Cancer, Gender, stage of disease, etc.

Fields where Research Design Used

These research designs can be used in various fields including;

Basic Science

Social sciences,

Education, healthcare,

Business

Systematic Process:

Knowledge / Information is normally based on;

●Beliefs, Intuitions & Opinions

Believing something does not make the knowledge true

A strong belief can also be turned false

If someone has an opposing belief than how can we decide Who is right and who is wrong??

In this case: A systematic Process is the best way to create knowledge

Research is a systematic and structured process of investigation and inquiry

•Aimed at discovering, interpreting, and revising knowledge or information.

Research involves:

1.Identifying a research question or problem

2.Conducting a literature review to understand existing knowledge

3.Designing a methodology to collect and analyze data

4.Collecting and analyzing data

5.Drawing conclusions and making recommendations

Also read: Introduction to Research 1st Lecture Slide by Dr. Ghazala Ali Khan

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For registration in 2nd Online course entitled as ” Nanoscience & Nanotechnology: From Basic to Advance”, click on this link.

For course schedule, click on this link. 

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THANK YOU PARTICIPANTS

On behalf of our team, IM Group of Researchers would like to thank you all for attending our advanced Ultrafiltration training session. We hope that you found the session informative and beneficial, and that it provided you with valuable insights and knowledge into the field of Ultrafiltration.

We appreciate your commitment to self-improvement and your dedication to enhancing your professional skills. We believe that you have made an excellent investment in your future by attending this training session, and we are confident that you will be able to apply the knowledge that you have gained to your future work projects.

We also appreciate the time and effort that you invested in the training session. We understand that your schedules are busy and that it can be challenging to take the time out of your busy lives to participate in such training sessions. Your eagerness to learn and your commitment to improving yourselves demonstrates your professionalism and your dedication to your craft.

Lastly, we would like to express our admiration for your enthusiasm and engagement during the training session. Your participation helped to make the session both informative and enjoyable for all attendees. We hope that you found the session engaging and interactive, and that you enjoyed the opportunity to network and exchange ideas with other professionals in your field.

Once again, we thank you for your participation, and we look forward to seeing the positive impact that the training session will have on your future work projects.

To check complete results, click here.

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