Research-ሪሰርች(ጁፒተር-Jupiter)
🔷 Business proposal 🔷 Proposal(Masters) 🔷 Research ማማከር 🔷 survey questionnaire ለማዘጋጀት እናማክራለን 🛑 ለተመራቂዎች ተማሪዎች ጥሩ ርዕሰ እንዴት መምረጥ እንዳለባችሁ እናማክራለን!
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام Research-ሪሰርች(ጁፒተር-Jupiter)
تُعد قناة Research-ሪሰርች(ጁፒተር-Jupiter) (@researchrc) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 15 274 مشتركاً، محتلاً المرتبة 13 160 في فئة التعليم والمرتبة 2 219 في منطقة Ethiopia.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 15 274 مشتركاً.
بحسب آخر البيانات بتاريخ 27 يوليو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -153، وفي آخر 24 ساعة بمقدار -5، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 13.63%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 4.35% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 2 083 مشاهدة. وخلال اليوم الأول يجمع عادةً 665 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 2.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل sample, population, anova, assumption, proposal.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“🔷 Business proposal
🔷 Proposal(Masters)
🔷 Research ማማከር
🔷 survey questionnaire ለማዘጋጀት እናማክራለን
🛑 ለተመራቂዎች ተማሪዎች ጥሩ ርዕሰ እንዴት መምረጥ እንዳለባችሁ እናማክራለን!”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 28 يوليو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
جاري تحميل البيانات...
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| 2 | MIXED RESEARCH METHODS
ውድ የቻናላችን ቤተሰቦች ዛሬ ስለ MIXED RESEARCH METHOD ዋና ዋና ነገሮችን እንመልከት ።
✅Mixed research በመጀመሪያ በSocial science/Educational Science በብዛት የሚተገበር ቢሆንም አሁን ግን በhealth science ዘርፍም በብዛት ይጠቀሙበታል ።
✅Mixed research ማለት በአንድ ጥናታዊ ጽሁፍ ውስጥ ሁለት መንገዶችን( Qualitative ና quantitative)በአንድ ላይ ስንጠቀምበት ነው።
♻️ይህም ሁለቱን እኩል(parallel)ወይም በተራ በተራ(sequential) በmixed research design መሰራት መጠቀም እንችላለን
❓ይህንን የreseach አይነት በብዛት በማስተርስ እና በፒ.ኤች.ዲ የትምህርት ደረጃ የሚጠቀሙበት ስሆን በመጀመሪያ ዲግሪ ግን በብዛት አይመከርም።
❓ሁለት የተለያዩ የreseach መንገዶችን በአንድ ላይ ለመጠቀም ከሌሎቹ በተለያ መንገድ ትንቃቄ እና እውቀት ሊጠይቅ ይችላል።
🥴በተለምዶ ሰዎች ሁለቱንም( qualitativeና quantitative መንገድ እጠቀማለሁ ስሉ እንሰማለን። ነገር ግን የmixed method ትክክለኛ መንገድ ሳይከተሉ ይቀሩና በመጨረሻ ላይ ስቸገሩ ያጋጥማል ።
👇ትክክለኛ mixed method core characteristics የሚከተሉት ናቻው።
1️⃣ ከmixed methods ውስጥ የትኛውን Design እንደምትጠቀሙ መግለጽ ያስፈልጋል። (concurrent triangulation, Sequential or embaded)
ይህም ብቻ አይደለም ለእያንደንዱ የትኛውን Design እንደምትጠቀሙ መግላጽ ያስፈልጋል ።
💠Qualitative (phenomenology, ethnography,..etc)
💠Quantitative (Cross sectional, Experimental, cohort... Etc)
ተብሎ ሊገለጽ ያስፈልጋል ።
2️⃣ ለሁሉቱም (qualitative & quantitative) ትክክለኛ methodology መከተል ያስፈልጋል ። Data collection method & materials, sample size, data analysis, ለሁለቱም በተገቢው መንገድ ልብራራ ይገባል። ይህም ለሁለቱም ለየብቻ ሊብራራ ግድ ነው።
3️⃣በሁለቱን መንገድ የተሰበሰበው Data (መርጃ) Analize መድረግ ያስፈልጋል። ለሁለቱም ለየብቻ Analysis መስራት ያስፈልጋል።
4️⃣ከሁለቱም የተገኛውን results ከግምት በማስገባት discussion ላይ መግላጽ ያስፈልጋል። ይህም የአንዱ result የሌለውን ይደግፈል ወይም አይደግፍም የሚለው ዋና የmixed method አላማ ነው። ከሁለቱም የተገኛውን ውጤት Triangulate ማድረግ ያስፈልጋል፣ ይህ የማይሆን ከሆነ mixed methods ፈይዳ የለውም።
⁉️ነገር ግን በጥናቱ የሚትጠቀሙበት mixed study design የሚወሰን ይሆናል። ምክንያቱም ለ Sequential እና ለ convergent ወይም ለ embaded ተመሳሳይ አይነት መንገድ አትከተሉም፣ methodology አጻጻፍ እንኳ በተወሰነ መልኩ ይላያያል።
ይቀጥላል...
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Consultancy on academic tasks such as:
✍️ Research title selection and concept not description;
✍️ Research proposal draft;
✍️ Thesis or research evaluations;
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✍️ any others questions related to research works, please contact us on Telegram.
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| 3 | Identification of a Research Problem
🍏The following steps are to be followed in identifying a research problem;
Step I Determining the field of research in which a researcher is keen to do the research work.
Step II The researcher should develop the mastery on the area or it should be the field of his specialization.
Step III He/She should review the research conducted in area to know the recent trend and studies are being conducted in the area.
Step IV On the basis of review, he/she should consider the priority field of the study.
Step V He/She should draw an analogy and insight in identifying a problem or employ his personal experience of the field in locating the problem. He/She may take help of supervisor or expert of the field.
Step VI He/She should pin point specific aspect of the problem which is to be investigated
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⌚️Assignment / አሳይመንት
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| 4 | RESEARCH PROPOSAL WRITING TEMPLATE
Title:
Your title should answer the question: What is your research about? It should be a short,
concise phrase. Narrow down to the specific area to manage in terms of resources
CHAPTER ONE: INTRODUCTION
1.1 Background of the study
✍️ The background explains in detail several components of the experiment that must be
included in any proposal.
✍️ After reading the introduction, the reader should conclude why the researcher is conducting the research and how this research will affect the
academic community and society at large.
✍️ It is sufficient to grab the reader’s attention, introduce the topic at hand, and provide a
brief definition of the theory from which the study is based.
✍️ The background section
outlines why you chose your topic.
✍️ Background section should include:
* what prompted your interest in the topic
* relevance to previous research (literature)
* what your research will contribute to the research and the field.
1.2 Statement of the problem
The “Statement of the Problem” is an imperative part of the proposal.
That is, in order for
research to be conducted; one must notice a problem in the existing literature that has
not been previously addressed.
For this section, the following questions should be answered:
• Why does this research study need to be conducted?
• What specific issues does this study raise that have not been observed in other literature pertaining to the topic?
Answering these questions will allow readers to understand why this particular study is
important and how the study will attempt to answer new, never-before asked questions.
In this section state how the problem is very serious.
Refer literature Quote research
conducted previously.
Include policy issues with regards of your title and your personal experiences and observation.
1.3 Basic Research questions
• What are the research questions you are trying to find the answer to?
• Frame 3-5 basic research questions
1.4 Objective of the research.
1.4.1 General objective
1.4.2 Specific objectives
1.5 Delimitation of the study
Delimitation means scope of your study. Indicate the areas you are going to study and
the issues to be included.
1.6 Limitation of the study
In this section explain the problems that you will face while conducting the research.
1.7 Organization of the study
Indicate in order the chapters and their detail information under each chapter.
1.8 Definition of key terms
It is essential that one defines the central ideas or concepts of the research study.
Therefore, carefully define each concept/variable that will be used in the study, citing other research studies as much as needed.
For college and University students (Degree, Masters and PhD programs), if you need support on academic tasks such as:
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| 5 | The main characteristics of a good sample
✍️ A good sample is the true representative of the population corresponding to its properties.
The population is known as aggregate of certain properties and sample is called sub-aggregate
of the universe.
✍️A good sample is free from bias, the sample does not permit prejudices th65e learning and pre-
conception, imaginations of the investigator to influence its choice.
✍️A good sample is an objective one, it refers objectivity in selecting procedure or absence of
subjective elements from the situation.
✍️ A good sample maintains accuracy. It yields an accurate estimates or statistics and does not
involve errors.
✍️A good sample is comprehensive in nature. This feature of a sample is closely linked with
true-representativeness. Comprehensiveness is a quality of a sample which is controlled by
specific purpose of the investigation. A sample may be comprehensive in traits but may not
be a good representative of the population.
✍️ A good sample is also economical from energy, time and money point of view.
✍️ The subjects of good sample are easily approachable. The research tools can be administered
on them and data can be collected easily.
✍️The size of good sample is such that it yields an accurate results. The probability of error
can be estimated.
✍️ A good sample makes the research work more feasible.
✍️ A good sample has the practicability for research situation.
If you need support related to:
⌚️Assignment / አሳይመንት
⌚️Research / ሪሰርች
⌚️Proposal / ፕሮፖዛል
⌚️Term Paper / ተረም ፔፐር
⌚️Case study/ ኬዝ ስተዲ
⌚️Article Review
⌚️Mini research
⌚️Business plan
🥭Training on basic statistical software's
🗝GIS
🗝 STATA
🗝 SPSS
🗝 R
🪜And other related software's...... also any other Questions please contact us via
☎️
+251912688642
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https://t.me/Research100stock
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| 6 | Assumptions of logistics regression
The main assumptions of logistic regressions are the following:
👉 For Binary dependent variable, the outcome variable must be binary (e.g., 0/1, Yes/No, Success/Failure).
👉 Independence of observations: Each observation should be independent of the others.
👉 Linearity of independent variables with the logit: The relationship between continuous predictors and the log-odds (logit) of the outcome must be linear. This does not mean the predictors must be linearly related to the outcome itself.
👉 multicollinearity among independent variables: Independent variables should not be highly correlated with each other. High multicollinearity inflates standard errors and weakens inference.
👉 Large sample size: Logistic regression requires a sufficiently large sample for stable estimates.
👉 Absence of strongly influential outliers: Extreme values can unduly influence model estimates.
Consultancy on academic tasks such as:
✍️ Research title selection and concept not description;
✍️ Research proposal draft;
✍️ Thesis or research evaluations;
✍️ Data analysis methods including SPSS, STATA, E-VIEWS, MATHLAB, R,
✍️ Quantitative data analysis and interpretation, and
✍️ any others questions related to research works, please contact us on Telegram.
✍ Data analysis using statistical softwares such as
🗝SPSS
🗝 STATA
🗝 AMOS
🗝 R
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| 7 | Assumptions of logistics regression
The main assumptions of logistic regressions are the following:
👉 For Binary dependent variable, the outcome variable must be binary (e.g., 0/1, Yes/No, Success/Failure).
👉 Independence of observations: Each observation should be independent of the others.
👉 Linearity of independent variables with the logit: The relationship between continuous predictors and the log-odds (logit) of the outcome must be linear. This does not mean the predictors must be linearly related to the outcome itself.
👉 multicollinearity among independent variables: Independent variables should not be highly correlated with each other. High multicollinearity inflates standard errors and weakens inference.
👉 Large sample size: Logistic regression requires a sufficiently large sample for stable estimates.
👉 Absence of strongly influential outliers: Extreme values can unduly influence model estimates.
Consultancy on academic tasks such as:
✍️ Research title selection and concept not description;
✍️ Research proposal draft;
✍️ Thesis or research evaluations;
✍️ Data analysis methods including SPSS, STATA, E-VIEWS, MATHLAB, R,
✍️ Quantitative data analysis and interpretation, and
✍️ any others questions related to research works, please contact us on Telegram.
✍ Data analysis using statistical softwares such as
🗝SPSS
🗝 STATA
🗝 AMOS
🗝 R
☎️
+251920256875
+251920256875
Telegram Account
https://t.me/Success_Research_Consultant
https://t.me/Success_Research_Consultant
Telegram
@success100research
@rese100arch
የመመረቂያ ጽሁፍ ለምትሰሩ (Research, Thesis, Dissertation),
We consult you!!!
የማማከር አገልግሎት እንሠጣለን።
Share for others!!! ለሌሎች ያጋሩ!! | 1 |
| 8 | Assumptions of logistics regression
The main assumptions of logistic regressions are the following:
👉 For Binary dependent variable, the outcome variable must be binary (e.g., 0/1, Yes/No, Success/Failure).
👉 Independence of observations: Each observation should be independent of the others.
👉 Linearity of independent variables with the logit: The relationship between continuous predictors and the log-odds (logit) of the outcome must be linear. This does not mean the predictors must be linearly related to the outcome itself.
👉 multicollinearity among independent variables: Independent variables should not be highly correlated with each other. High multicollinearity inflates standard errors and weakens inference.
👉 Large sample size: Logistic regression requires a sufficiently large sample for stable estimates.
👉 Absence of strongly influential outliers: Extreme values can unduly influence model estimates.
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| 9 | SUCCESS RESEARCH CONSULTANT
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| 11 | لا يوجد نص... | 2 514 |
| 12 | Reliability and validity
🍎Reliability and validity are two key concepts in research methodology, particularly in the context of measuring instruments, such as surveys, tests, or questionnaires. They are used to assess the quality and rigor of a research study or measurement tool.
✍️Reliability
👍Reliability refers to the consistency and stability of a measure. A reliable instrument produces similar results under consistent conditions.
Types of Reliability:
👍Test-Retest Reliability: Measures the consistency of results when the same test is administered to the same group at different times.
👍 Inter-Rater Reliability: Assesses the degree of agreement between different raters or observers.
👍Internal Consistency Reliability: Evaluates the consistency of items within a test (e.g., Cronbach's Alpha).
👍Parallel-Forms Reliability: Measures the correlation between two equivalent versions of a test.
How to Test Reliability:
🌱Use statistical measures like Cronbach's Alpha (for internal consistency), Pearson's correlation coefficient (for test-retest reliability), or Cohen's Kappa (for inter-rater reliability).
🌱A reliability coefficient of 0.7 or higher is generally considered acceptable.
🌎Validity
👉🏿Validity refers to the extent to which a tool measures what it is intended to measure. A valid instrument accurately reflects the concept it is supposed to measure.
Types of Validity:
🤙Content Validity: Ensures the test covers all aspects of the concept being measured.
🤙Construct Validity: Assesses whether the test measures the theoretical construct it claims to measure.
🤙 Convergent Validity: Measures how closely the test is related to other tests that measure the same
construct.
🤙 Discriminant Validity: Ensures the test is not related to measures of different constructs.
🤙 Criterion Validity: Evaluates how well the test predicts or correlates with a criterion.
🤙 Concurrent Validity: Measures how well the test correlates with a criterion measured simultaneously.
🤙 Predictive Validity: Assesses how well the test predicts future outcomes.
How to Test Validity:
✏️ Use expert reviews for content validity.
✏️ Conduct factor analysis or correlation studies for construct validity.
✏️ Compare the test results with an established criterion for criterion validity.
🍏Key Differences:
💎Reliability is about consistency (does the test produce stable results?).
💎Validity is about accuracy (does the test measure what it claims to measure?).
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| 13 | How to ensure reliability of data for a research?
In research, ensuring the reliability of data means making sure the data are consistent, accurate, and dependable over time and across measurements.
The main ways to ensure data reliability include the following.
✍️ Use Standardized Data Collection Methods:
Use well-designed questionnaires or instruments with clear instructions.
✍️ Ensure Instrument validation:
* Use validated and tested instruments (established surveys).
* Conduct reliability tests such as: Test–retest reliability (consistency over time), Inter-rater reliability (consistency between observers), Internal consistency (e.g., Cronbach’s alpha).
✍️ Train Data Collectors
# Provide proper training and guidelines to enumerators or researchers.
# Reduce interviewer bias by ensuring uniform understanding of questions.
✍️ Pilot Testing (Pre-testing)
@ Conduct a pilot study to identify unclear questions or errors.
@ Revise tools based on pilot feedback before full data collection.
✍️ Data Cleaning and Validation
Check for: Missing values, Outliers, duplicate entries
✍️ Use Multiple Data Sources (Triangulation)
Compare data from different sources, methods, or respondents.
✍️ Ethical and Honest Reporting
Avoid data fabrication or selective reporting.
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