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Month: January 2024

How do I choose the correct statistical test?

How do I choose the correct statistical test?

Choosing the correct statistical analysis is crucial for obtaining meaningful and valid results in a research study. Here are some steps to guide you in selecting the appropriate statistical analysis: Define Your Research Question: Clearly articulate your research question or hypothesis. The nature of your question will influence the type of statistical analysis needed. Questions generally fall into one of three types: descriptive, correlational/predictive and cause/effect or experimental. Understand Your Data: Examine the characteristics of your data, including the type…

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What are best practices for dealing with missing data?

What are best practices for dealing with missing data?

Dealing with missing data is a critical aspect of statistical analysis, and it requires careful consideration to ensure the validity and reliability of study results. Here are some best practices for handling missing data: Understand the Mechanism of Missingness: Determine whether the missing data is missing completely at random (MCAR), missing at random (MAR), or missing not at random (MNAR). Understanding the mechanism can guide the choice of appropriate imputation methods. Explore Patterns of Missing Data: Examine patterns of missingness…

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What is effect size?

What is effect size?

The concept of effect size is crucial in interpreting the practical significance of statistical results. Effect size measures the magnitude or strength of the relationship or difference observed in a statistical analysis. It provides a standardized way to quantify the extent to which a particular phenomenon or intervention has an impact in the population. In the context of biostatistics, effect size is often used to express the size of a treatment effect, the strength of an association between variables, or…

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What is the Independent t-test?

What is the Independent t-test?

The independent t-test, also known as the two-sample t-test, is a statistical method used to compare the means of two independent groups to determine if there is a significant difference between them. It is commonly used in research and experimental studies to assess whether the means of two groups are statistically different from each other. The key assumptions of the independent t-test include: Normal Distribution: The data within each group should be approximately normally distributed. Homogeneity of Variances: The variances…

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