Refer to the following list of the number of years that Olympic gold medalists in various sports lived after winning their first gold medal. Assume that the data represent samples from a larger population.

Years lived after winning gold:

$\text{23, 31, 45, 18, 29, 37, 50, 42, 33, 27, 39, 41, 46, 30}$

What is the level of measurement of the data (nominal , ordinal, interval, ratio)?

The following data set shows the weights (in kilograms) of $12$ randomly selected backpacks carried by university students:

$7$, $12$, $9$, $15$, $20$, $17$, $11$, $14$, $10$, $9$, $12$, $9$

Find $Q_1$, $Q_2$ and $Q_3$.

Refer to the following list of years that former CEOs of major technology companies lived after their official retirement: $18$, $22$, $15$, $30$, $12$, $25$, $40$, $14$, $20$, $28$, $35$, $50$.

Identify any outliers in the dataset using the interquartile range ($\text{IQR}$) method.

Refer to the scatterplot provided below:

After identifying the $10$ data points represented in the scatterplot, calculate the correlation coefficient ($r$). Based on the value of $r$, determine whether there is a linear correlation between the two variables.