- We are given the equation:
\[ 40\% \text{ of } 70\% \text{ of } P = 35\% \text{ of } R\% \text{ of } Q \]
- Additionally, we know:
\[ P\% \text{ of } P\% \text{ of } 400 = 16 \]
Express the second equation as:
\[ \frac{P}{100} \times \frac{P}{100} \times 400 = 16 \]
Simplifying:
\[ \frac{P^2}{10000} \times 400 = 16 \] \[ \frac{P^2}{25} = 16 \] \[ P^2 = 400 \implies P = 20 \]
The first equation becomes:
\[ 40\% \times 70\% \times 20 = 35\% \times R\% \times Q \]
Converting percentages to decimals:
\[ 0.4 \times 0.7 \times 20 = 0.35 \times \frac{R}{100} \times Q \]
Simplifying:
\[ 0.4 \times 0.7 \times 20 = 5.6 \] \[ 5.6 = 0.35 \times \frac{R \times Q}{100} \]
Multiplying both sides by 100:
\[ 560 = 0.35 \times R \times Q \]
Dividing both sides by 0.35:
\[ R \times Q = 1600 \]
The product is:
\[ P \times Q \times R = 20 \times 1600 = 32,000 \]
Conclusion: The product of \( P \), \( Q \), and \( R \) is 32,000.
List-I | List-II |
---|---|
(A) Confidence level | (I) Percentage of all possible samples that can be expected to include the true population parameter |
(B) Significance level | (III) The probability of making a wrong decision when the null hypothesis is true |
(C) Confidence interval | (II) Range that could be expected to contain the population parameter of interest |
(D) Standard error | (IV) The standard deviation of the sampling distribution of a statistic |