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If a researcher needs to assess whether there is a significant difference between the means of two groups to test a hypothesis, which statistical method would they employ?
  • a)
    Chi-square test
  • b)
    Correlation coefficient
  • c)
    Sign-test
  • d)
    Student’s t-test 
Correct answer is option 'D'. Can you explain this answer?
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If a researcher needs to assess whether there is a significant differe...
To assess whether there is a significant difference between the means of the two groups, a researcher would typically use the Student's t-test. This statistical method is designed to compare the means of two independent groups to determine if they are significantly different from each other.
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If a researcher needs to assess whether there is a significant differe...
Understanding the Student's t-test
The Student’s t-test is a statistical method used to determine if there is a significant difference between the means of two groups. This test is particularly useful in hypothesis testing where the researcher wants to compare the averages of two distinct populations.
When to Use a t-test
- Two Groups: It is specifically designed for scenarios involving two groups, which can be independent (different subjects) or paired (same subjects under different conditions).
- Normal Distribution: The data in each group should ideally follow a normal distribution, especially when sample sizes are small.
- Equal Variance: Assumes that both groups have approximately equal variances, although variations of the t-test (like Welch's t-test) can be used if this assumption is violated.
Key Features of the t-test
- Hypothesis Testing: The t-test helps in testing the null hypothesis, which states that there is no significant difference between the group means.
- P-value Calculation: It generates a p-value that indicates the probability of observing the data if the null hypothesis is true.
- Effect Size: Provides insights into the magnitude of the difference, not just whether it is statistically significant.
Other Options Explained
- Chi-square test: Used for categorical data to assess relationships between variables.
- Correlation coefficient: Measures the strength and direction of a linear relationship between two variables, not differences in means.
- Sign-test: A non-parametric test used for comparing paired samples, but not specifically for means of two independent groups.
In summary, the Student's t-test is the appropriate choice for researchers assessing mean differences between two groups, making it a fundamental tool in statistical analysis.
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