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Correlation Coefficient Video Lecture | Quantitative Aptitude for CA Foundation

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FAQs on Correlation Coefficient Video Lecture - Quantitative Aptitude for CA Foundation

1. What is the correlation coefficient in the context of the CA Foundation exam?
Ans. The correlation coefficient is a statistical measure that quantifies the strength and direction of the linear relationship between two variables. In the CA Foundation exam, it is used to understand the degree of association between different financial and accounting variables.
2. How is the correlation coefficient calculated in the CA Foundation exam?
Ans. The correlation coefficient can be calculated using the formula: r = (Σ((X - X̄) * (Y - Ȳ))) / (sqrt(Σ(X - X̄)^2) * sqrt(Σ(Y - Ȳ)^2)) Where X and Y represent the values of two variables, X̄ and Ȳ represent their respective means, and Σ denotes summation. This formula helps determine the correlation coefficient, denoted by 'r', which ranges from -1 to 1.
3. What does a correlation coefficient of 0 indicate in the CA Foundation exam?
Ans. A correlation coefficient of 0 in the CA Foundation exam indicates that there is no linear relationship between the two variables being analyzed. This means that changes in one variable do not correspond to any predictable changes in the other variable.
4. How is the strength of the correlation determined based on the correlation coefficient in the CA Foundation exam?
Ans. Generally, the strength of the correlation is determined by the absolute value of the correlation coefficient (r). If |r| is close to 1, it suggests a strong correlation, while a value closer to 0 indicates a weak correlation. However, it is essential to consider other factors and conduct a thorough analysis to draw meaningful conclusions.
5. Can the correlation coefficient be negative in the CA Foundation exam? If so, what does it indicate?
Ans. Yes, the correlation coefficient can be negative in the CA Foundation exam. A negative correlation coefficient (r) suggests an inverse relationship between the two variables being studied. It means that as one variable increases, the other variable tends to decrease, and vice versa. This negative correlation can be valuable in financial analysis and decision-making processes.
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