Research-ሪሰርች(ጁፒተር-Jupiter)

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 🙏🙏🙏🙏🙏🙏🙏🙏

Correlation Analysis * This is one of the commonly used research analysis method. * Correlation is used to describe the relationship or association between two variables. * It tells the direction and magnitude of relationship of events or variables. * Some of most commonly used correlation types are Pearson's correlation coefficient for continuous  variable and Spearman correlation for ordinal or ranked data. * If the sign of the correlation is positive, the variables are linearly correlated, and if it is negative, the relationship is reversed. * The degree or magnitude of relationship is commonly specified as: # Very low if r is below 0.2. # Low if r is in 0.2-0.39 # Medium if r is in 0.4- 0.59 range. # High if r is above 0.6-0.79. #  Very high or strong relationship if r is above 0.8. * As the value of the correlation close to 1, the relationship is strong. * As r goes to 0, poor relationship. * The coefficient of determination tells us the relationship in percentage and it is calculated as r square times 100. For college and University students (Degree, Masters and PhD programs), if you need support on academic tasks such as: # article reviews # term papers #  Case studies # project work Research related tasks # title selection # title description and concept note # research  proposal # Research for graduation # Mini research # business  plan # project  proposals # Data analysis (SPSS, STATA, ...) and others, contact on 0920256875 0918533959 Telegram Account https://t.me/Success_Research_Consultant

Research Hypotheses and Research Questions 🍏Research hypotheses are predictive statements about the relationship between variables. 🍏Research questions are similar to hypotheses, except that they do not entail specific predictions and are phrased in question format. For example, one might have the following research question: "Is there a difference in students' scores on a standardized test if they took two tests in one day versus taking only one test on each of two days?" 🍎A hypothesis regarding the same issue might be: "Students who take only one test per day will score better on standardized tests than will students who take two tests in one day." We divide research questions into three broad types: difference, associational, and descriptive. 👍Difference research questions: For these questions, we compare scores (on the dependent variable) of two or more different groups, each of which is composed of individuals with one of the values or levels on the independent variable. This type of question attempts to demonstrate that groups are not the same on the dependent variable. 👍Associational research questions: are those in which two or more variables are associated or related. This approach usually involves an attempt to see how two or more variables covary (as one grows larger, the other grows larger or smaller) or how one or more variables enables one to predict another variable. 👍Descriptive research questions: are not answered with inferential statistics. They merely describe or summarize data, without trying to generalize to a larger population of individuals. continue………………………………. For college and University students (Degree, Masters and PhD programs), if you need support on academic tasks such as: # article reviews # term papers #  Case studies # project work Research related tasks # title selection # title description and concept note # research  proposal # Research for graduation # Mini research # business  plan # project  proposals # Data analysis (SPSS, STATA, ...) and others, Training on basic statistical software's     🗝GIS                🗝  STATA                                  🗝 SPSS                                                🗝 R                                                         🗝 XLSTAT 🪜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 🙏🙏🙏🙏🙏🙏🙏🙏🙏

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... #share others contact us +251920256875 በቴሌግራም አካውንት ያግኙን! https://t.me/Success_Research_Consultant 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!!

Multiple regression assumptions diagnostic How can we test regression assumptions? Before performing regression analysis, it is important to check regression assumptions like multicollinerity, normality, linearity, autocorrelation, and homoskasticity. 1. Normally distribution It refers to the normal distribution of residuals or error terms. It can be tested using either graphical methods by histogram, predicted probability (p-p) plots and plotted points or statistical methods by using kurtosis and skewness values. Statistical methods are better than graphical methods. A data is normally distributed when the skewness and kurtosis values are between -2 and 2. 2. Multicollinearity It refers to the relationship between independent variables or predictors. That is, predictors should not be highly correlated. It can be checked by using either correlation coefficient between independent variables, using Tolerance and variance inflation factors (VIF) values of variables or eigenvalue values. That is, there is no multicollinearity among independent variables (multicollinearity assumption is not violated) if the correlation coefficient is less than 0.8 or tolerance is above 0.1 and VIF is below 5. 3. Linearity It refers to the linear relationship between independent and outcome variables. In a scatter plot, linearity can be checked if points conform to a diagonal fitted line. If the assumption of multicollinearity and normality are not violated, don't worry about linearity. 4. Homoscedasticity Homoscedasticity refers to the constant variance of error terms. Its opposite is heteroscedasticity. If it fails (heteroscedastic), additional predictors are required to explain results, or transform the data using logarithm, square root, .... Homoscedastic if residuals evenly distributed between -2 and 2. 5. Autocorrelation It refers to independence of observation. The independent variable is said to be autocorrelated when the current value of Y is dependent on its previous value. It can be checked by using Durbin-Watson test (DW). If DW = 2 or approaches to 2, there is no autocorrelation. እናማክራለን For college and University students (Degree, Masters and PhD programs), if you need support on academic tasks such as: # article reviews # term papers #  Case studies # project work Research related tasks # title selection # title description and concept note # research  proposal # Research for graduation # Mini research # business  plan # project  proposals # Data analysis (SPSS, STATA, ...) and others, Training on basic statistical software's     🗝GIS                🗝  STATA                                  🗝 SPSS                                                🗝 R                                                         🗝 XLSTAT 🪜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 🙏🙏🙏🙏🙏🙏🙏🙏🙏

የትኛው አይነት የሪሰርች ጥያቄ (research question) ወይም Dependent Variable ምን አይነት Analysis ያስፈልጋል ብለን ስንመለከት 1. Dependent Variable በቁጥር የሚገለጽ(Numerical variable)  ከሆነ  በብዛት የሚንጠቀምበት Analysis models:-   🔢 bivariate correlation (Pearson, partial etc..)   🔢 Linear regression( simple, multiple LR)   🔢 t- tests (one sample, paired, independent t test)   🔢 ANOVA (one way, two way, ANCOVA, MANOVA...) የሚባሉ ሞዴሎች ሲሆን 2. Dependent variable Categorical ከሆነ    ⏸ chi square test    ⏸ Logistic regression( BLR, MLR, OLR) በአብዛኛው ጊዜ የሚንጠቀምባቸው ናቸው። ለጥናትና ምርምርዎ እገዛ ይፈልጋሉ?     አዎ ከሆነ መልስዎ! በመንግስትም ሆነ በግል ዩኒቨርሲቲ/ኮሌጅ በዲፕሎማ፣ዲግሪ እና በማስተርስ ፕሮግራም ለምትማሩ እና ትምህርታችሁን ጨርሳችሁ የምርቃት ጊዜያችሁን በጉጉት ለምትጠብቁ ሁሉ ስለ ጥናትና ምርምር በቂ እዉቀትን በመያዝ የመመረቂያ ፅሁፋችሁን ተመራጭ እና ተወዳጅ አድርጋችሁ በመስራት በጥሩ ዉጤት ትመረቁ  ዘንድ እናግዝዎታለን፡፡ ማለትም:- 👉ስለ Research አሰራር ማገዝ 👉ስለ ጥናትና ምርምርዎ Proposal አዘገጃጀት ማገዝ 👉Power point ማዘጋጀት 👉የMatlab software የሚጠይቁ ጥናቶችን ማገዝ 👉በSPSS STATA software የሚሰሩ ጥናቶችን  ማገዝ 👉የተሰሩ ጥናቶችን Comment  ማድረግ 👉Business plan ማዘጋጀት 👉Article Review ማዘጋጀት 👉የተለያዩ  Assignment በጥራት መስራት 👉Case Study ስልክ :- +251920256875,  contact US @success100research @success100research @success100research @success100research

🍎Panel logistic regression🍏 👍Panel logistic regression, also known as fixed-effects logistic regression or conditional logistic regression, is a statistical method used to analyze panel or longitudinal data where the dependent variable is binary (i.e., it takes on two possible values) and there are repeated observations on the same individuals over time. 👍Panel data refers to a dataset that contains observations on the same individuals or entities over multiple time periods. Examples of panel data include tracking individuals' health outcomes over time, analyzing financial data of companies over several years, or examining the voting behavior of individuals across multiple elections. 👍Logistic regression, on the other hand, is a statistical model used to estimate the probability of a binary outcome based on one or more independent variables. It is commonly used when the dependent variable is dichotomous, such as predicting whether a customer will churn or not, or whether a patient will respond to a particular treatment or not. 👍Panel logistic regression extends logistic regression to account for the panel structure of the data. It incorporates fixed effects, which capture individual-specific heterogeneity that is constant over time but may affect the outcome variable. By including fixed effects, panel logistic regression controls for unobserved individual-level characteristics that may be correlated with the dependent variable. 👍The fixed effects in panel logistic regression are typically included as dummy variables for each individual in the panel. These fixed effects capture the individual-specific intercepts and allow for the estimation of time-varying effects of the independent variables on the dependent variable. 👍Panel logistic regression can provide insights into how individual characteristics and time-varying factors influence the probability of the binary outcome. It is often used in various fields, including economics, social sciences, and public health, to analyze longitudinal data and understand the determinants of binary outcomes over time. 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

STATEMENT OF PROBLEM IN RESEARCH © Statement of the problem needs to discuss the practical problems that you have observed or get in the form of feedback concerning the topic that you are interested in doing the investigation. © In addition, you need to do an empirical review related to your topic and identify the gap that needs to be filled. Research gap/ literature gap @ It is based on review of theoretical and empirical literature. @ Research gap refers to: ® Unavailability of studies on the issue of the study. ® Presence of very few studies on the issue under study. ® Lack of outdated studies on the issue of study. ® Due to conflicting findings on the issue under investigation. ® Practical problems noticed in an entity with no explanation of it in the empirical studies. Conceptual framework Conceptual/theoretical framework of the study indicates the relationship   between variables. The conceptual framework should show a diagrammatically demonstration of the relationship between the Independent and dependent variables. የማማከር አገልግሎት እንሰጣለን ✍️ Research title selection and concept note 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 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 🙏🙏🙏🙏🙏🙏🙏🙏

RESEARCH Plagiarism When does your paper contain plagiarism? Plagiarism involves 1. Intentionally copying/using someone's ideas or words or statements without acknowledge them (with no proper citation). 2. Cutting/copying and pasting text or note from internet and using as your own work. 3. Purchasing someone's work and describing it as your own work. 4. Citing a source but reproducing the exact word/Statement without quotation marks. 5. Borrowing the structure of another author's phrases/sentences without giving the source. 6. Borrowing all or part of another paper. Note that plagiarism above 20% is not allowed for Masters thesis paper and above 35% is not permitted for PhD dissertation paper. Research designs + Research design is an arrangement of conditions for collection and analysis of data based on purpose of the study. + It constitutes the blue print for the collection, measurement and analysis of data aimed at answering specific research questions. + There are different research designs. + The selection of a research design depends on its purpose. + Some of commonly mentioned research designs are:        Qualitative Designs Phenomonology Ethnography  Historical            Quantitative Experimental Cross-sectional Cohort Explanatory Quasi-experimental Descriptive 1. Descriptive research design # It emphasis on determining the frequency with which something occurs or the extent to which two variables are correlated. # It tries to discover answers to the question who, what, when, where, and sometimes how. # It clearly describes a situation or behavior obtained at a particular time. 2. Explanatory research design @ It investigates whether the value of one variable causes or determines the value of other variable. @ It assesses relationship between variables in order to explain certain problems or events. @ It attempts go explain the reasons for the phenomenon. @ It uses theories or hypotheses to study about forces that  caused a certain phenomenon to occur. @ It focuses on relationship between variables. @ It uses different models of relationship. 3. Experimental research design = It focuses on testing the change of variables by considering at least two groups (both experimental. = It usually involves practical measurement of data using various methods. = It is based on the principle of randomization. That is, to be representative, experiments should be done on random samples. Consultancy SERVICES የማማከር አገልግሎት For College and University students, who are attending Bachelor Degree, and Masters Degree programs, if you need supports and consultancy on academic tasks such as: * Article review methods; * Term paper organization; * Case study preparation; * Project proposals; * Research title selection and concept note description; * Research proposal draft; * Research writing methods for graduation programs; * Thesis or research evaluations; * Research work procedures; * Mini research works; * Data analysis methods including SPSS, STATA, E-VIEWS, MATHLAB, R, AMOS;  * Quantitative data analysis and interpretation, and * Any others questions related to research works, please contact us and share it for your friends. TELEGRAM CHANNEL    https://t.me/Success_Research_Consultant Contact Via telegram accounts @success100research @rese100arch Phone 0920256875 WE ARE READY TO CONSULT IN YOUR RESEARCH WORK. በቅንነት ለጓደኞችዎ ያጋሩ የማማከር አገልግሎት እንሰጣለን

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 🙏🙏🙏🙏🙏🙏🙏🙏

Correlation Analysis * This is one of the commonly used research analysis method. * Correlation is used to describe the relationship or association between two variables. * It tells the direction and magnitude of relationship of events or variables. * Some of most commonly used correlation types are Pearson's correlation coefficient for continuous  variable and Spearman correlation for ordinal or ranked data. * If the sign of the correlation is positive, the variables are linearly correlated, and if it is negative, the relationship is reversed. * The degree or magnitude of relationship is commonly specified as: # Very low if r is below 0.2. # Low if r is in 0.2-0.39 # Medium if r is in 0.4- 0.59 range. # High if r is above 0.6-0.79. #  Very high or strong relationship if r is above 0.8. * As the value of the correlation close to 1, the relationship is strong. * As r goes to 0, poor relationship. * The coefficient of determination tells us the relationship in percentage and it is calculated as r square times 100. For college and University students (Degree, Masters and PhD programs), if you need support on academic tasks such as: # article reviews # term papers #  Case studies # project work Research related tasks # title selection and concept note # research  proposal # Research for graduation # Mini research # business  plan # project  proposals # Data analysis (SPSS, STATA, ...) and others, contact on 0920256875 Telegram Account https://t.me/Success_Research_Consultant

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A brief mention of the important sample designs is as follows: 👍a. Deliberate sampling: Deliberate sampling is also known as purposive or non-probability sampling. This sampling method involves purposive or deliberate selection of particular units of the universe for constituting a sample which represents the universe. When population elements are selected for inclusion in the sample based on the ease of access, it can be called convenience sampling. 👍b. Simple random sampling: This type of sampling is also known as chance sampling or probability sampling where each and every item in the population has an equal chance of inclusion in the sample and each one of the possible samples, in case of finite universe, has the same probability of being selected. 👍c.Systematic sampling: In some instances the most practical way of sampling is to select every 15th name on a list, every 10th house on one side of a street and so on. Sampling of this type is known as systematic sampling. An element of randomness is usually introduced into this kind of sampling by using random numbers to pick up the unit with which to start. This procedure is useful when sampling frame is available in the form of a list. 👍d.Stratified sampling: If the population from which a sample is to be drawn does not constitute homogeneous group, then stratified sampling technique is applied so as to obtain representative sample. In this technique, the population is stratified into a number of non-overlapping subpopulations or strata and sample items are selected from each stratum. 👍e. Quota sampling: In stratified sampling the cost of taking random samples from individual strata is often so expensive that interviewers are simply given quota to be filled from different strata, the actual selection of items for sample being left to the interviewer judgment. 👍f. Cluster sampling and area sampling: Cluster sampling involves grouping the population and then selecting the groups or the clusters rather than individual elements for inclusion in the sample. Suppose some departmental store wishes to sample its credit card holders. 👍g. Multi-stage sampling: This is a further development of the idea of cluster sampling. This technique is meant for big inquiries extending to a considerably large geographical area like an entire country. Under multi-stage sampling the first stage may be to select large primary sampling units such as states, then districts, then towns and finally certain families within towns. 👍h. Sequential sampling: This is somewhat a complex sample design where the ultimate size of the sample is not fixed in advance but is determined according to mathematical decisions on the basis of information yielded as survey progresses. This design is usually adopted under acceptance sampling plan in the context of statistical quality control. 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

COMMON ERRORS IN LITERATURE WRITING The following points are considerable common errors in writing research work. 👉 Review is not logically organized; 👉 Review is not focused on most important facets of the study; 👉 Review does not relate literature to the study; 👉 Too few references are cited; 👉 Outdated references cited; 👉 Review is not written in author’s own words; 👉 Review reads like a series of disjointed summaries; 👉 Review does not argue a point; and 👉 Recent references are omitted.                   SAMPLING PROCESS The sampling process comprises several stages: # Defining the population of concern; # Specifying a sampling frame, a set of 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; and # Reviewing the sampling process Consultancies SERVICES የማማከር አገልግሎት For College and University students, who are attending Bachelor Degree, and Masters Degree programs, if you need supports and consultancy on academic tasks such as: * Article review methods; * Term paper organization; * Case study preparation; * Project proposals; * Research title selection and concept note description; * Research proposal draft; * Research writing methods for graduation programs; * Thesis or research evaluations; * Research work procedures; * Mini research works; * Data analysis methods including SPSS, STATA, E-VIEWS, MATHLAB, R, AMOS;  * Quantitative data analysis and interpretation, and * Any others questions related to research works, please contact us and share it for your friends. TELEGRAM CHANNEL    https://t.me/Success_Research_Consultant Contact Via telegram accounts @success100research @rese100arch Phone 0920256875 WE ARE READY TO CONSULT IN YOUR RESEARCH WORK. በቅንነት ለጓደኞችዎ ያጋሩ

ANOVA and MANOVA 🍎ANOVA (Analysis of Variance) and MANOVA (Multivariate Analysis of Variance) are statistical methods used to analyze differences between groups. Both methods are commonly used in social, behavioral, and biological research to compare means across different groups. ✍️ANOVA is used when there is only one dependent variable, and the independent variable has two or more levels. ✍️It tests whether there are significant differences in the means of the dependent variable across the levels of the independent variable. ✍️ ANOVA assumes that the dependent variable is normally distributed and that the variances of the groups are equal. 🍏MANOVA, on the other hand, is used when there are two or more dependent variables. It tests whether there are significant differences in the means of the dependent variables across the levels of the independent variable. 🌱MANOVA is a multivariate extension of ANOVA, and it allows researchers to test for differences in multiple dependent variables simultaneously. 🌱MANOVA assumes that the dependent variables are normally distributed and that the covariance matrices of the groups are equal. ለጥናትና ምርምርዎ እገዛ ይፈልጋሉ?     አዎ ከሆነ መልስዎ! በመንግስትም ሆነ በግል ዩኒቨርሲቲ/ኮሌጅ በዲግሪ እና በማስተርስ ፕሮግራም ለምትማሩ እና ትምህርታችሁን ጨርሳችሁ የምርቃት ጊዜያችሁን በጉጉት ለምትጠብቁ ሁሉ ስለ ጥናትና ምርምር በቂ እዉቀትን በመያዝ የመመረቂያ ፅሁፋችሁን ተመራጭ እና ተወዳጅ አድርጋችሁ በመስራት በጥሩ ዉጤት ትመረቁ  ዘንድ እናግዝዎታለን፡ If you need support related to:     1 Research / ሪሰርች 3 Proposal / ፕሮፖዛል 4 Term Paper /  ተረም ፔፐር 5 Case study/ ኬዝ ስተዲ 6 Article Review 7  Mini research 8  Business plan Any other Questions ይደውሉ +251920256875 በቴሌግራም አካውንት ያግኙን https://t.me/Success_Research_Consultant

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

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