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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)
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tips to help you develop an effective thesis title:

☄️Be clear and concise: A good thesis title should clearly convey the topic and main focus of your research in a concise manner. Avoid using vague or overly complicated language.

☄️Reflect the content and scope: The title should accurately reflect the content and scope of your thesis. It should give readers a clear idea of what to expect from your research.

☄️Use keywords: Including relevant keywords in your title can help potential readers and researchers find your thesis when searching for related topics. Consider using words or phrases that are commonly used in your field.

☄️Be specific: A specific title is more informative and engaging than a general one. Instead of a broad topic, try to narrow down your focus and highlight a specific aspect or angle of your research.

☄️Highlight the novelty or significance: If your research has a unique or groundbreaking aspect, consider incorporating it into your title.

☄️Seek feedback: Share your potential title with your advisor, peers, or colleagues to get their input.

☄️Consider the tone and style: The tone of your title should align with the conventions of your field.

☄️Be honest and accurate: Make sure your title accurately represents the content of your thesis. Avoid using sensationalized or misleading titles that may create false expectations.

☄️Revise and refine: Don't be afraid to revise and refine your title as you progress with your research.
☄️Check formatting guidelines: If you have specific formatting guidelines for your thesis, such as those provided by your university or department, make sure your title adheres to those requirements.
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STATISTICAL MEASURES IN RESEARCH

# Statistical measures are classified in to two classes: Parametric and Non-Parametric measures.

# The category of the two classes is based on its assumptions and techniques.
# The researcher can determine the statistical analysis method based on the data, objective and samples.

# Some characteristics of parametric and non-parametric statistics are discussed below.

1. Parametric statistical measures

Parametric statistics make assumptions about a sample or a population including:

@ Make assumptions about a population;
@ Make normality assumptions of a population or data;
@ Used in interval or ratio scales (continuous data);
@ Requires not too small sample size (30 and above);
@ Used when a data set meets the required assumptions for different techniques;

Parametric measures include t-test types (simple t-test, independent t-test and paired t-test), Analysis of variance/ANOVA/ types (One way ANOVA, two-way ANOVA, and MANOVA), correlation, linear regression, etc.

2. Non-Parametric statistical measures

Some of the characteristics of non-parametric statistics are listed below:
* Do not have assumptions about a population;
* It is a free test (no normality assumption of a population or a data);
* Measures in nominal (categorical) or ordinal (ranked) scales;
* Used when you have small sample size (below 30);
* Used when the data do not meet the assumptions of parametric techniques;
* Its major assumptions are random sampling and independent observation (each case or person counted only once);
* Used when there is large variation in a data set.

Non-parametric measures are mentioned below (with their parametric alternatives in brackets).
❤ Chi-square test of goodness (no parametric alternative).
❤ Chi-square test of independence (Pearson test of correlation).
❤ Mann-Whitney U test (independent t-test).
❤ Will Coxon Signed Rank test (paired t-test).
❤ Kruscal-Wallis test (one way between groups ANOVA).
❤ Friedman test (one-way repeated measures ANOVA).
❤ Logistics regressions (linear regressions).

The detail explanations, assumptions, characteristics, analysis, interpretations, and usages will be discussed in the next successive posts. 

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Consultant services

For College and University students, who are attending Bachelor Degree, and Masters programs, if you need supports and consultancy on academic tasks such as:


👍 Article review methods;
👍 Case study preparation;
👍 Project proposals;
👍 Business plan;
👍 Research title selection and concept not description;
👍 Research proposal draft;
👍 Research for graduation programs;
👍 Thesis or research evaluations;
👍 Research work procedures;
👍 Mini research works;
👍 Data analysis methods including SPSS, STATA, E-VIEWS, MATHLAB, R,
👍 Quantitative data analysis and interpretation, and any others questions related to research works,

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