document.write( "<A HREF=/cgi-bin/jump-to-question.mpl?question=1193729>Question 1193729</A>: <I><SPAN STYLE=\"word-break: break-all;\"> 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.   </SPAN>\n" );
document.write( "</I><HR><TABLE width=100%><TR><TD><B><A HREF=http://www.algebra.com/>Algebra.Com's</A> Answer #848529 by </B><A HREF=/tutors/aboutme.mpl?userid=parmen><B>parmen(42)</B></A><img src=\"/images/stars/stars-07.gif\" alt=\"\" >&nbsp;<A HREF=/tutors/aboutme.mpl?userid=parmen><IMG SRC=http://www.algebra.com/images/aboutme-small.gif BORDER=0 alt=\"About Me\" VALIGN=MIDDLE></A>&nbsp;<IMG SRC=http://www.algebra.com/images/nopicture.jpg><BR>You can <A HREF=\"/cgi-bin/embed-solution.mpl?show=1&solution=848529\">put this solution on YOUR website!</A><BR><SPAN STYLE=\"word-break: break-all;\"> **1. Calculate the total value of coins:**\r<BR>\n" );
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document.write( "* 9 coins * 1 euro/coin = 9 euros<BR>\n" );
document.write( "* 10 coins * 2 euros/coin = 20 euros<BR>\n" );
document.write( "* Total value = 9 euros + 20 euros = 29 euros\r<BR>\n" );
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document.write( "**2. Calculate the average money lost before lunch:**\r<BR>\n" );
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document.write( "* **Possible Scenarios:**<BR>\n" );
document.write( "    * All 6 coins are 1 euro: Loss = 6 euros<BR>\n" );
document.write( "    * All 6 coins are 2 euros: Loss = 12 euros <BR>\n" );
document.write( "    * Combinations of 1 euro and 2 euro coins: Loss can vary between 6 and 12 euros\r<BR>\n" );
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document.write( "* **Average Loss Before Lunch:** <BR>\n" );
document.write( "    * To find the exact average, we would need to consider all possible combinations of coins lost. <BR>\n" );
document.write( "    * However, we can estimate the average loss as: (6 euros + 12 euros) / 2 = 9 euros\r<BR>\n" );
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document.write( "**3. Calculate the average money lost after lunch:**\r<BR>\n" );
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document.write( "* **Possible Scenarios:**<BR>\n" );
document.write( "    * All 7 coins are 1 euro: Loss = 7 euros<BR>\n" );
document.write( "    * All 7 coins are 2 euros: Loss = 14 euros<BR>\n" );
document.write( "    * Combinations of 1 euro and 2 euro coins: Loss can vary between 7 and 14 euros\r<BR>\n" );
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document.write( "* **Average Loss After Lunch:** <BR>\n" );
document.write( "    * Similar to before lunch, we can estimate the average loss as: (7 euros + 14 euros) / 2 = 10.5 euros\r<BR>\n" );
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document.write( "**4. Dispersion (This requires more information)**\r<BR>\n" );
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document.write( "* **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. <BR>\n" );
document.write( "    * **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.\r<BR>\n" );
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document.write( "**5. Correlation Coefficient (Difficult to Determine in this Case)**\r<BR>\n" );
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document.write( "* **Correlation** measures the relationship between two variables. <BR>\n" );
document.write( "* In this scenario, it's difficult to define a meaningful correlation. <BR>\n" );
document.write( "    * 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. \r<BR>\n" );
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document.write( "**Key Considerations:**\r<BR>\n" );
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document.write( "* **Simplifications:** The calculations above make some simplifying assumptions. In reality, the actual losses would vary based on the specific coins lost each day.<BR>\n" );
document.write( "* **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.\r<BR>\n" );
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document.write( "**Note:** This analysis provides a basic framework. For a more precise and comprehensive analysis, further information and statistical methods would be required.<BR>\n" );
document.write( " </SPAN>\n" );
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