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In the Name of the Almighty

About Shadi Noroozi:


πŸ”ΈRanked πŸ₯‡ in the PhD Entrance Examination

πŸ”ΉRanked Fifth in the MA Entrance Exam

πŸ”ΈRecipient of Talented Student Awards in BA, MA, and PhD and Distinguished Student

πŸ”ΉUniversity Lecturer (University of Tehran and Sharif university)

πŸ”ΈPeer Reviewer for Academic Journals
Unlock Your Research Potential!

Welcome to my channel, where research meets statistics! I'll guide you through integrating these two powerful tools to elevate your studies and projects. Plus, I offer personalized consultations to help you achieve your goals.

Stay tuned for expert insights and actionable tips. join my community to stay ahead in the world of research and statistics!
Ever wondered where knowledge comes from? πŸ€” Let's explore the sources of knowledge, starting with authority, tradition, and personal experiences.

Authority πŸ“š: Information provided by experts in a particular field, giving credibility and reliability to the knowledge being shared.

Tradition 🌎: The knowledge passed down through generations, shaping our beliefs and practices based on cultural heritage.

Personal Experience πŸ’‘: Learning from our own experiences.

These sources help us build a foundation for understanding and decision-making! πŸ“ˆ

But one Question

Are these sources reliable?

#KnowledgeSources
Ever heard of deductive reasoning and syllogism? πŸ€”

Deductive Reasoning πŸ’‘: A method where conclusions are drawn from general principles or premises. It's like building a logical bridge from broad ideas to specific conclusions! πŸŒ‰

Syllogism πŸ“: A specific form of deductive reasoning that consists of:

Major Premise πŸ“š: A general statement.

Minor Premise πŸ“: A specific statement related to the major premise.

Conclusion 🎯: The logical outcome derived from the premises.

Example:
Major Premise: All humans are mortal.
Minor Premise: Socrates is human.
Conclusion: Therefore, Socrates is mortal. πŸ’­

πŸ’ͺ #DeductiveReasoning #Syllogism
The Limitations of Deductive Reasoning 🚨.

To arrive at true conclusions, one must begin with true premises πŸ’‘.

However, establishing the universal truth of many statements can be challenging πŸŒͺ️.

This makes deductive reasoning insufficient as a source of new knowledge πŸ“š.

For example, in the Middle Ages, people substituted dogma for true premises , leading to invalid conclusions 🚫.

Francis Bacon (1561–1626) was the first to call for a new approach to knowing πŸ”, emphasizing the importance of empirical evidence and observation .

#DeductiveReasoning #Limitations
Revolutionizing Knowledge: The Power of Inductive Reasoning 🌟

Bacon believed that investigators should not accept premises handed down by the Church Fathers as absolute truth πŸ™…β€β™‚οΈ.

Rather, investigators should establish conclusions based on facts gathered through direct observation πŸ”.

In Bacon’s system, an investigator made observations on particular events in a class or category, and then made inferences about the whole class or category on the basis of the observations πŸ“Š.

This approach is called inductive reasoning πŸ“š.

It is the reverse of deductive reasoning πŸ”„.

Exclusive use of induction resulted in the accumulation of isolated facts and information that made little contribution to the advancement of knowledge πŸ“Š.

#InductiveReasoning #Bacon
The Birth of the Inductive-Deductive Method: A Scientific Revolution 🌟

In the 19th century, scholars combined the strengths of inductive and deductive reasoning to create a powerful new technique: the inductive-deductive method, or the scientific approach πŸ“š.

Charles Darwin's Pioneering Work 🌿:

Inductive Beginnings: Darwin initially used inductive reasoning to gather observations, but this alone wasn't enough 🌱.

Adding Deductive Power: By incorporating hypotheses to explain his findings, Darwin's work became more productive. He then tested these hypotheses by making deductions and gathering additional data πŸ”¬.

This integrated approach, later endorsed by John Dewey, became known as the scientific method 🎯. It revolutionized scientific inquiry by allowing researchers to both generate new theories and test existing ones 🌈.

#ScientificMethod #InductiveDeductive #CharlesDarwin
🀩1πŸ‘Œ1
Researchers' Assumptions and Attitudes πŸ”

When conducting research, scientists rely on certain assumptions and attitudes to guide their work.
Let's explore the assumptions and attitudes that guide scientists:

Assumptions:
1. Determinism: Events are lawful and ordered, not random 🌐.

2. Empiricism: Knowledge comes from empirical evidence πŸ”¬.

Attitudes:
1. Skepticism: Doubting until verified πŸ“Š.

2. Objectivity: Keeping biases at bay πŸ“.

3. Focus on Facts: Separating data from moral judgments πŸ“Š.

These principles are crucial not just in science, but in any field where data-driven decisions are key. How do you ensure objectivity and skepticism in your work? Share your insights! πŸ’¬

#ResearchMethods #ResearcherAttitude
Challenges in Conducting Scientific Research in Education and Social Sciences🌟

Ever wondered why research in education and social sciences is so complex? πŸ€” Let's explore some of the key challenges:

Complexity of Subject Matter🌎: Unlike natural sciences, social sciences deal with human behavior, which varies greatly across individuals and groups. Generalizations can be risky due to these differences.

Difficulties in ObservationπŸ”: Observations in social sciences require interpretation, making them less objective. Motives and attitudes are not directly observable, leading to subjective interpretations.

Replication ChallengesπŸ”„: Unlike chemistry experiments, social phenomena cannot be precisely replicated. Each study is unique, making it hard to confirm findings across different contexts.

Observer-Subject Interaction πŸ“Š: The act of observation itself can change the behavior being studied, as seen in the Hawthorne effect. This complicates drawing clear conclusions.

Control and Measurement Issues πŸ“: Controlling variables and measuring outcomes in social sciences is more challenging than in natural sciences. Tools for measurement are less precise, and past influences on behavior can't be directly measured.

Ethical and Legal Considerations 🚫: Research involving human subjects must adhere to strict ethical and legal guidelines, limiting the types of studies that can be conducted.

Despite these challenges, researchers continue to innovate and adapt, using multiple methods to ensure robust findings 🌈.

How do you navigate these complexities in your research?

#ResearchChallenges #SocialSciences #EducationResearch #ScientificMethod
Unlocking the Language of Research: Constructs and Variables πŸ”“

Ever wondered how researchers decode complex phenomena? πŸ€” Let's dive into the world of constructs and variables!

ConstructsπŸ’‘
These are abstract ideas that help us interpret data and build theories (e.g., intelligence, motivation, anxiety) 🧠.

Constitutive Definition: A general meaning, like a dictionary entry πŸ“š.

Operational Definition: Specifies how to measure or manipulate a construct in research, ensuring everyone's on the same page πŸ“Š.

Variables
These are measurable characteristics or constructs that can change across different people or things (e.g., height, weight, test scores) πŸ“Š.

Researchers study the relationships between variables to uncover insights and patterns πŸ”.

#ConstructsAndVariables #ScientificInquiry #ResearchTips
πŸ” Mastering Variables in Research:

The Building Blocks of Study Design
Variables are the heartbeat of research! πŸ§ͺ

Whether you’re studying human behavior, plant growth, or test scores, understanding variables is key to designing robust studies. Let’s break it down:

What is a Variable?
A variable is a characteristic, construct, or attribute that can take different values across people, things, or time.


1⃣Independent Variable (Cause 🎯):
The factor you manipulate to observe its effect.
Example: Study time (hours) βž” Impact on test scores.
2️⃣ Dependent Variable (Effect πŸ“Š):
The outcome you measure.
Example: Test scores βž” Affected by study time
πŸ”Έ Categorical Variables (Groups 🏷️):
Binary: Yes/No, Pass/Fail.
Nominal: Unordered groups (e.g., country of birth).

πŸ”ΈOrdinal: Ranked groups (e.g., customer satisfaction: Poor β†’ Excellent).

πŸ”Έ Continuous Variables (Measurements πŸ“ˆ):
Infinite values within a range (e.g., age, temperature, income).

πŸ”΄Confounding Variables (⚠️ Sneaky Influencers):
Unaccounted factors that distort results (e.g., stress levels affecting study outcomes).


#ResearchMethods #VariablesInResearch
πŸ‘Œ2
Variables can be split into categorical and continuous, and within these types there are different levels of measurement:

1⃣Categorical (entities are divided into distinct categories):

πŸ”ΈBinary variable:
There are only two categories
(e.g. dead or alive).


πŸ”ΈNominal variable: There are more than two categories (e.g. whether someone is an omnivore, vegetarian, vegan, or fruitarian).

πŸ”ΈOrdinal variable: The same as a nominal variable but the categories have a logical order (e.g. whether people got a fail, a pass, a merit in their exam).
2⃣Continuous (entities get a distinct score):

πŸ”ΉInterval variable: Equal intervals on the variable represent equal differences in the property being measured

(e.g. the difference between 8 and 10 is equivalent to the difference between 17 and 19).

πŸ”ΉRatio variable:
The same as an interval variable, but the ratios of scores on the scale must also make sense
(e.g. a score of 24 on an anxiety scale means that the person is, in reality, twice as anxious as someone scoring 12).
What is the process to make a decision when it comes to statistics?

Let's dive in!

The journey begins with observation.

Start by identifying areas where a problem might exist. This initial step is crucial as it sets the stage for further investigation and analysis.

Then, you should set about asking questions
Exploring Research Approaches: Quantitative, Qualitative, and Mixed Methods πŸ”
Let's dive into the world of research methods and explore how each approach helps us understand different phenomena:

Quan (the one in red)

*Qual (the one in blue)