⚛In the #Repeated Measures window we have to specify in the right order a dependent variable for each #Within-Subjects Variables. 

For instance, In our SPSS ♎️sample dataset, we have three dependent variables representing three periods: 1st Period, 2nd Period, and 3rd Period. In our study, these 

The #1st Period will be moved to the #_?_(1) position, the #2nd Period to the _?_(2) position, the #3rd Period to _?_(3), and so on. You can select each variable and use the arrow to move it in the appropriate box or even easier, use the mouse to drag and drop each dependent variable to its appropriate position. 
see figure below👇👇👇👇

Add the Within-Subjects Variable in SPSS

Add plotting

⚛Options for ANOVA with repeated measures analysis
Finally, on the #Repeated Measures window, click #OK to proceed with the ANOVA for repeated measures analysis in SPSS👏

♎️RESULTS, when we look at the mean between the groups for each diet program,
♐️we can observe that the mean for #Low Carbs Diet group is lower than that of the# Low Fat Diet group which may indicate that a low carbs diet program is more efficient –
with the exception of #1st Period where the means between the two programs are the closest!!

♓️The Estimated Margin Means table shows us an estimate summary for the mean and standard error for each period as well as the lower and upper bound values at a 95% confidence interval.
🕎we can observe that the #Mean in the Estimates table is actually the equivalent of the #Total Mean in the Descriptive Statistics table ከላይ ማለት ነው።

♎️Finally, the #Multivariate Test table shows us a similar output as the Multivariate Test 🕎we discussed above tabel and shows statistical significance for all the different test statistics used in the ANOVA for repeated measures analysis.
@Setotaw CONSULTING 2022
♎️♎️♎️♎️♎️END♊️♊️♊️♊️

☸☸☸☸☸References♓️♓️♓️
Fench , D. (2022). Discovering statistics using IBM SPSS statistics (5th edition). Sage: Thousand Oaks, CA.

Pallant, J. (2010). SPSS survival manual: A step-by-step guide to data analysis using SPSS. Maidenhead: Open University Press/McGraw-Hill.

Pituch, K.A. and Stevens, J.P. (2016) Applied Multivariate Statistics for the Social Sciences.
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♎️#Add and subscription♒️
ያስፈልጋል

በግዜ እጥረት እና በመሳሰሉት ምክንያቶች ትምህርታችሁ ላይ እገዛ የምትፈልጉ ተመራቂዎችን
Research ከtitle መረጣ እስከ ማጠቃለያ (Discussion, conclusion and recommendations) ድረስ እናግዛለን።
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የ Software አቅርቦት
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Theoretical & conceptual frameworks

The terms theoretical framework and conceptual framework are often used interchangeably to mean the same thing. Although they are both used to understand a research problem and guide the development, collection, and analysis of research, it's important to understand the difference between the two. #When working on coursework or dissertation #research, make sure to clarify what is being asked and any specific course or program requirements.
ብዘውን ግዜ explanatory reserch design ያላቸው ጥናታዊ ፅሁፍ ይጠቀሙበታል።

2.RESEARCH DESIGN
#Explanatory Research DESIGN
፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨፨
Explanatory research is a systematic approach to understanding events, behaviors, or situations. It involves identifying a problem or issue and then collecting data in an effort to explain why it exists.

#Explanatory research can be used to identify the causes of problems or to understand the factors that influence behavior. In many cases, explanatory research is used to develop hypotheses that can be tested through experimentation.

#Explanatory Research Data Collection Methods
Common data collection methods in Explanatory Research are:
-Literature reviews
-Interviews 
-Focus groups
-Pilot studies
-Observations
-Experiments


1.Literature reviews
A literature review is a critical summary of what the scientific literature says about your specific topic or question. It is a written overview of the current state of research on a given topic, and it usually appears as part of a larger research project, such as a dissertation.
A literature review has three main purposes:
1. To survey the current state of knowledge on a topic
2. To identify gaps in the existing research
3. To provide context for a new research project
2.Interviews
In explanatory research, interviews are used to gather information from individuals about their experiences, opinions, and behaviors. This type of research is typically used to understand why people do what they do and how they think about certain issues.
3.Focus groups
Focus groups are an important tool in the explanatory research process. search, Focus groups help researchers understand people’s opinions and attitudes on a particular issue. They also provide insights into how people think and feel about certain topics.
Focus groups are usually small, with 6-10 participants. This allows for a more intimate setting where people can feel comfortable sharing their thoughts and opinions.
3.Pilot studies
Pilot studies are small-scale, preliminary research investigations. They are conducted to explore the feasibility of a larger study and to gather preliminary data. Pilot studies in explanatory research help researchers to refine their hypothesis and research design.
4.Observations
In explanatory research, observations are made in order to get a clear understanding of a phenomenon.
This type of research is often used in the sciences, as it allows for the collection of data that can be used to explain a certain event or natural occurrence.
There are two main types of observations in Explanatory Research:
Qualitative
Quantitative

፨፨፨፨፨፨፨፨፨፨፨፨፨፨
Qualitative observations are those that are made without the use of numbers or measurements. They are often more subjective and can be more difficult to analyze.
Quantitative observations are those that involve some form of measurement. These types of observations are often easier to analyze, but can sometimes be less accurate than qualitative ones.
Experiments(መኩራ)
Experiments in explanatory research are designed to provide information about causal relationships. These studies test hypotheses about how certain independent variables affect dependent variables.
Explanatory Research Data Analysis Methods
There are many methods of data analysis used in explanatory research. Some common methods are:
Regression Analysis
Chi-Square Test
T-Test
ANOVA
Regression Analysis
Regression analysis is a method of data analysis that is used to predict the relationship between two or more variables. This method is used to determine the strength of the relationship between the variables and to identify any trends.
Chi-Square Test
The chi-square test is a statistical test that is used to determine if there is a significant difference between two or more groups. This test is used to compare categorical data.
T-Test
The T-test is a statistical test that is used to compare means between two groups. This test can be used to compare data that are not normally distributed.