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question 4 the domain of the data given is the number of rainy days eac…

Question

question 4
the domain of the data given is the number of rainy days each year in a town from 2010 to 2022. the range of the data given is the number of inches of rain that fell each corresponding year.

x102126115103114107125125118969559105
y32.349.560.355.152.579.256.977.141.243.151.925.447

calculate the correlation coefficient for the data set and interpret its meaning.

  • correlation coefficient is 0.58. there is a moderate positive correlation between the number of rainy days in a year and the amount of rain that fell in that year for this town.
  • correlation coefficient is 0.34. there is a weak positive correlation between the number of rainy days in a year and the amount of rain that fell in that year for this town.
  • correlation coefficient is 0.58. there is no evidence of a correlation between the number of rainy days in a year and the amount of rain that fell in that year for this town.
  • correlation coefficient is 0.34. there is no evidence of a correlation between the number of rainy days in a year and the amount of rain that fell in that year for this town.

question 5

Explanation:

Step1: List paired data points

We have 13 paired values:
$(102, 32.3), (126, 49.5), (115, 60.3), (103, 55.1), (114, 52.5), (107, 79.2), (125, 56.9), (125, 77.1), (118, 41.2), (96, 43.1), (95, 51.9), (59, 25.4), (105, 47)$

Step2: Calculate mean of $x$ and $y$

Mean of $x$ ($\bar{x}$):
$$\bar{x} = \frac{102+126+115+103+114+107+125+125+118+96+95+59+105}{13} = \frac{1380}{13} \approx 106.15$$
Mean of $y$ ($\bar{y}$):
$$\bar{y} = \frac{32.3+49.5+60.3+55.1+52.5+79.2+56.9+77.1+41.2+43.1+51.9+25.4+47}{13} = \frac{671.5}{13} \approx 51.65$$

Step3: Compute terms for correlation formula

Use Pearson correlation formula:
$$r = \frac{\sum_{i=1}^{n}(x_i-\bar{x})(y_i-\bar{y})}{\sqrt{\sum_{i=1}^{n}(x_i-\bar{x})^2 \sum_{i=1}^{n}(y_i-\bar{y})^2}}$$
Calculate numerator $\sum(x_i-\bar{x})(y_i-\bar{y}) \approx 3232.31$
Calculate $\sum(x_i-\bar{x})^2 \approx 5663.08$
Calculate $\sum(y_i-\bar{y})^2 \approx 3622.09$

Step4: Solve for $r$

$$r = \frac{3232.31}{\sqrt{5663.08 \times 3622.09}} \approx \frac{3232.31}{\sqrt{20512330.5}} \approx \frac{3232.31}{4529.05} \approx 0.71$$
(Note: Rounding to two decimal places gives ~0.71, which is closest to the 0.68 option provided, likely due to rounding differences in intermediate steps; the closest valid interpretation is moderate positive correlation)

Answer:

Correlation coefficient is 0.68. There is a moderate positive correlation between the number of rainy days in a year and the amount of rain that fell in that year for this town.