Research-ሪሰርች(ጁፒተር-Jupiter)

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          +251912688642 Telegram Account           https://t.me/Research100stock           https://t.me/Research100stock

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!!

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!!

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!!

SUCCESS RESEARCH CONSULTANT ሰክሰስ የጥናትና ምርምር ስራዎች አማካሪ 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!!

SUCCESS RESEARCH CONSULTANT ሰክሰስ የጥናትና ምርምር ስራዎች አማካሪ 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!!

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?). 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 +251912688642 Telegram Account https://t.me/Research100stock https://t.me/Research100stock 👇👇👇👇👇👇👇👇 join and learn more https://t.me/star_research_consultancy 🙏🙏🙏🙏🙏🙏🙏🙏

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. 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!!

Classification of Research based on Application: 🍏a. Pure / Basic / Fundamental Research: As the term suggests a research activity taken up to look into some aspects of a problem or an issue for the first time is termed as basic or pure. It involves developing and testing theories and hypotheses that are intellectually challenging to the researcher but may or may not have practical application at the present time or in the future. The knowledge produced through pure research is sought in order to add to the existing body of research methods. Pure research is theoretical but has a universal nature. It is more focused on creating scientific knowledge and predictions for further studies. 🍏b. Applied / Decisional Research: Applied research is done on the basis of pure or fundamental research to solve specific, practical questions; for policy formulation, administration and understanding of a phenomenon. It can be exploratory, but is usually descriptive. The purpose of doing such research is to find solutions to an immediate issue, solving a particular problem, developing new technology and look into future advancements etc. This involves forecasting and assumes that the variables shall not change. Key Differences between Basic and Applied Research ✍️a) Basic Research can be explained as research that tries to expand the already existing scientific knowledge base. On the contrary, applied research is used to mean the scientific study that is helpful in solving real-life problems. ✍️b) While basic research is purely theoretical, applied research has a practical approach. ✍️c) The applicability of basic research is greater than the applied research, in the sense that the former is universally applicable whereas the latter can be applied only to the specific problem, for which it was carried out. ✍️d) The primary concern of the basic research is to develop scientific knowledge and predictions. On the other hand, applied research stresses on the development of technology and technique with the help of basic science. ✍️e) The fundamental goal of the basic research is to add some knowledge to the already existing one. Conversely, applied research is directed towards finding a solution to the problem under consideration. 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 +251912688642 Telegram Account https://t.me/Research100stock https://t.me/Research100stock 👇👇👇👇👇👇👇👇 join and learn more https://t.me/star_research_consultancy 🙏🙏🙏🙏🙏🙏🙏🙏

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Research design 👍Research design is a comprehensive plan for data collection in an empirical research project. It is a “blueprint” for empirical research aimed at answering specific research questions or testing specific hypotheses, and must specify at least three processes: (1) the data collection process, (2) the instrument development process, and (3) the sampling process. 🍏Broadly speaking, data collection methods can be broadly grouped into two categories: positivist and interpretive. 👍 Positivist methods, such as laboratory experiments and survey research, are aimed at theory (or hypotheses) testing, while interpretive methods, such as action research and ethnography, are aimed at theory building. Positivist methods employ a deductive approach to research, starting with a theory and testing theoretical postulates using empirical data. 👍In contrast, interpretive methods employ an inductive approach that starts with data and tries to derive a theory about the phenomenon of interest from the observed data. 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 +251912688642 Telegram Account https://t.me/Research100stock https://t.me/Research100stock 👇👇👇👇👇👇👇👇 join and learn more https://t.me/star_research_consultancy 🙏🙏🙏🙏🙏🙏🙏🙏

SUCCESS RESEARCH CONSULTANT ሰክሰስ የጥናትና ምርምር ስራዎች አማካሪ 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!!

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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?). 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 +251912688642 Telegram Account https://t.me/Research100stock https://t.me/Research100stock 👇👇👇👇👇👇👇👇 join and learn more https://t.me/star_research_consultancy 🙏🙏🙏🙏🙏🙏🙏🙏

SUCCESS RESEARCH CONSULTANT ሰክሰስ የጥናትና ምርምር ስራዎች አማካሪ 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!!