Math Problem Statement

y: x: 3444 11 3924 3.1 3114 1.1 3135 3.8 2650 8.4 2355 3.3 1993 5.8 1593 6 1533 3.2 1103 5.4 881 4.6 856 9.1 798 6.2 682 14.7 588 7.3 520 16.9 447 12.7 406 10.3 402 16.6 403 24.3 388 15.7 382 19.4 427 18.1 409 20.4 370 20.8 335 22.4 354 24.4 429 26.6 461 26.7 610 25.4 900 28.1 1186 25.1 1373 24.9 1520 22.7 1671 25.1 1738 21.9 2096 26.2 2222 20.7 2068 16.4 1694 16.2 1224 18.6 961 11.9 1056 16.1 1006 22.7 967 12.4 1023 9.5 1346 11.4 1647 2.4 1887 10.1 2209 9.1 3089 9.4 3822 3.4 4721 6.4 calculate pearson correlation coefficient

Solution

The Pearson correlation coefficient between the variables yy and xx is approximately 0.498-0.498. This indicates a moderate negative correlation, suggesting that as xx increases, yy tends to decrease.

Would you like to explore more details about this correlation or any related concepts? Here are some questions you might consider:

  1. What are the implications of a negative correlation in practical terms?
  2. How is the Pearson correlation coefficient calculated mathematically?
  3. What other correlation coefficients are there, and how do they differ from Pearson's?
  4. How can we visualize this correlation using a scatter plot?
  5. What are some potential factors that could influence the relationship between yy and xx?

Tip: Always visualize data relationships with plots to gain better insights!

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Math Problem Analysis

Mathematical Concepts

Statistics
Correlation

Formulas

Pearson correlation coefficient formula: r = (n(Σxy) - (Σx)(Σy)) / sqrt([nΣx^2 - (Σx)^2][nΣy^2 - (Σy)^2])

Theorems

Properties of correlation coefficients

Suitable Grade Level

Grades 10-12