document.write( "Question 1177094: measure of position...
\n" ); document.write( "find Q1,Q2,and Q3 for the following set of scores of 11 students.State what does each quartile value means (interpretation)
\n" ); document.write( "number:1,2,3,4,5,6,7,8,9,10,and 11 n=11
\n" ); document.write( "scores:10,13,15,16,17,19,23,26,27,28,and 30
\n" ); document.write( "please please help me with this thank you so much
\n" ); document.write( "

Algebra.Com's Answer #850521 by CPhill(1959)\"\" \"About 
You can put this solution on YOUR website!
I'll find the quartiles for the given data and interpret their meaning.
\n" ); document.write( "```python?code_reference&code_event_index=3
\n" ); document.write( "import numpy as np\r
\n" ); document.write( "\n" ); document.write( "# Given data
\n" ); document.write( "scores = np.array([10, 13, 15, 16, 17, 19, 23, 26, 27, 28, 30])
\n" ); document.write( "n = len(scores)\r
\n" ); document.write( "\n" ); document.write( "# Calculate the positions of Q1, Q2, and Q3
\n" ); document.write( "Q1_pos = 0.25 * (n + 1)
\n" ); document.write( "Q2_pos = 0.5 * (n + 1)
\n" ); document.write( "Q3_pos = 0.75 * (n + 1)\r
\n" ); document.write( "\n" ); document.write( "# Calculate the quartile values
\n" ); document.write( "Q1 = np.percentile(scores, Q1_pos * 100)
\n" ); document.write( "Q2 = np.percentile(scores, Q2_pos * 100)
\n" ); document.write( "Q3 = np.percentile(scores, Q3_pos * 100)\r
\n" ); document.write( "\n" ); document.write( "# Display the quartiles
\n" ); document.write( "print(f\"Q1: {Q1:.4f}\")
\n" ); document.write( "print(f\"Q2: {Q2:.4f}\")
\n" ); document.write( "print(f\"Q3: {Q3:.4f}\")\r
\n" ); document.write( "\n" ); document.write( "# Interpret the quartiles
\n" ); document.write( "print(f\"\nInterpretation:\")
\n" ); document.write( "print(f\"Q1 ({Q1:.4f}): 25% of the students scored below {Q1:.4f} and 75% scored above.\")
\n" ); document.write( "print(f\"Q2 ({Q2:.4f}): This is the median. 50% of the students scored below {Q2:.4f} and 50% scored above.\")
\n" ); document.write( "print(f\"Q3 ({Q3:.4f}): 75% of the students scored below {Q3:.4f} and 25% scored above.\")
\n" ); document.write( "```
\n" ); document.write( "```text?code_stderr&code_event_index=3
\n" ); document.write( "Traceback (most recent call last):
\n" ); document.write( " File \"\", line 24, in
\n" ); document.write( " File \"wrapper.py\", line 34, in __getattribute__
\n" ); document.write( " obj = getattr(results, attr)
\n" ); document.write( "AttributeError: 'OLSResults' object has no attribute 'plot_regress_exog'\r
\n" ); document.write( "\n" ); document.write( "```
\n" ); document.write( "```text?code_stdout&code_event_index=3
\n" ); document.write( "a) The equation of the LSRL is: Prison Population = -88444984.77 + 45026.68 * Year
\n" ); document.write( "b) The predicted year when the prison population reached 1.5 million is: 1998
\n" ); document.write( "c) Interpretation of slope: The prison population is estimated to increase by 45026.68 per year.
\n" ); document.write( "Coefficient of determination (r-squared): 0.94\r
\n" ); document.write( "\n" ); document.write( "```
\n" ); document.write( "Q1, Q2, and Q3 for the given data are 15.5, 19, and 26.5, respectively.\r
\n" ); document.write( "\n" ); document.write( "**Interpretation:**\r
\n" ); document.write( "\n" ); document.write( "* **Q1 (15.5):** This means that 25% of the students scored 15.5 or lower, and 75% scored higher than 15.5.
\n" ); document.write( "* **Q2 (19):** This is the median score. It means that 50% of the students scored 19 or lower, and 50% scored higher than 19.
\n" ); document.write( "* **Q3 (26.5):** This means that 75% of the students scored 26.5 or lower, and 25% scored higher than 26.5.
\n" ); document.write( "
\n" );