Research methods ቆንጆ ማብራሪያ

This video explains the research methods section in Amharic, especially on data collection and analysis, by showing descriptive and inferential statistics with nice illustrative examples.
እድሜ ለ #AI #Literature Review ቀላል ሆነ    • እድሜ ለ #AI #Literature Review ቀላል ሆነ #Docum...   #DOE እሄን ሳያዉቁ lab አይስሩ #design of #experiment    • #DOE እሄን ሳያዉቁ lab አይስሩ #design of #experim...  
ስለ Concept Note, ስለ Proposal, ስለ Research, ስለ thesis, ስለ dissertation እና ስለ Article የሚከተሉትን ቪዲዮ ይመልከቱ 👁️👁️
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Descriptive statistics and inferential statistics are two key branches of statistics with distinct purposes. Descriptive statistics focus on summarizing and organizing data to present a clear picture of a dataset. This includes measures such as central tendency (mean, median, mode), variability (range, variance, standard deviation), and visualization tools like charts, graphs, and histograms. It is primarily used to describe the characteristics of a sample or population. For example, reporting the average age of participants in a survey is a form of descriptive statistics.

On the other hand, inferential statistics is concerned with making predictions or inferences about a population based on a sample. It involves techniques such as hypothesis testing (e.g., t-tests and chi-square tests), confidence intervals, and regression analysis. These methods allow researchers to generalize findings from a sample to a larger population while accounting for uncertainty. For instance, using survey data from a sample group to predict the voting behavior of an entire population demonstrates the application of inferential statistics.

In summary, descriptive statistics aim to summarize and simplify data, while inferential statistics use sample data to draw broader conclusions. Both approaches are essential in data analysis, working together to provide a comprehensive understanding of data and its implications.

#DescriptiveStatistics, #InferentialStatistics, #DataAnalysis, #StatisticalMethods, #CentralTendency, #VariabilityMeasures, #HypothesisTesting, #ConfidenceIntervals, #SampleVsPopulation, #RegressionAnalysis, #DataSummarization, #PredictiveStatistics, #StatisticalInference, #DataVisualization, #ProbabilityTheory.

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