SOLUTION: Every morning John likes to take 9 coins each worth 1 euro and 10 coins - each 2 euro. Everyday before lunch he loses 6 coins and after lunch - 7 coins. Find how much money John lo

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Question 1193729: Every morning John likes to take 9 coins each worth 1 euro and 10 coins - each 2 euro. Everyday before lunch he loses 6 coins and after lunch - 7 coins. Find how much money John loses before and after lunch average, dispersion and correlation coefficient.
Answer by parmen(42)   (Show Source): You can put this solution on YOUR website!
**1. Calculate the total value of coins:**
* 9 coins * 1 euro/coin = 9 euros
* 10 coins * 2 euros/coin = 20 euros
* Total value = 9 euros + 20 euros = 29 euros
**2. Calculate the average money lost before lunch:**
* **Possible Scenarios:**
* All 6 coins are 1 euro: Loss = 6 euros
* All 6 coins are 2 euros: Loss = 12 euros
* Combinations of 1 euro and 2 euro coins: Loss can vary between 6 and 12 euros
* **Average Loss Before Lunch:**
* To find the exact average, we would need to consider all possible combinations of coins lost.
* However, we can estimate the average loss as: (6 euros + 12 euros) / 2 = 9 euros
**3. Calculate the average money lost after lunch:**
* **Possible Scenarios:**
* All 7 coins are 1 euro: Loss = 7 euros
* All 7 coins are 2 euros: Loss = 14 euros
* Combinations of 1 euro and 2 euro coins: Loss can vary between 7 and 14 euros
* **Average Loss After Lunch:**
* Similar to before lunch, we can estimate the average loss as: (7 euros + 14 euros) / 2 = 10.5 euros
**4. Dispersion (This requires more information)**
* **Dispersion** measures how spread out the data is. To calculate dispersion, we would need to know the probability distribution of losing each type of coin.
* **Standard Deviation:** If we had the probability distribution, we could calculate the standard deviation of the losses before and after lunch, which would give us a measure of dispersion.
**5. Correlation Coefficient (Difficult to Determine in this Case)**
* **Correlation** measures the relationship between two variables.
* In this scenario, it's difficult to define a meaningful correlation.
* The loss before lunch and the loss after lunch are not directly related in a way that allows us to calculate a meaningful correlation coefficient.
**Key Considerations:**
* **Simplifications:** The calculations above make some simplifying assumptions. In reality, the actual losses would vary based on the specific coins lost each day.
* **Probability Distribution:** To get more accurate results for average loss, dispersion, and potentially correlation, we would need to know the probability of losing each type of coin (1 euro or 2 euros) before and after lunch.
**Note:** This analysis provides a basic framework. For a more precise and comprehensive analysis, further information and statistical methods would be required.

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