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QUESTION 1 The Senator of Azenator State, is worried about the rising numbers in high blood pressure related deaths in his Jurisdiction and wants an end to this canker. A reputable medical research officer has claimed that, the situation is probably as a result of the ageing population of his State. The blood pressures, Y (mmHg), and Ages, X (years) of 10 hospital patients were sampled from Azenator State and summarized below. Patient A B C D E F G H I J Age (X) in Years 20 25 50 30 45 60 10 15 35 70 BP(Y) in (mmHg) 80 85 125 90 100 135 80 70 100 140 NB: Approximate to 2 decimal places Use the table to answer the questions that follow; i) Calculate the product moment correlation coefficient for the data and interpret your result. (3 Marks) ii) If the Senator decides to purchase and distribute Norvasc (a medicine that reduces blood pressure), based on your results in (i), which age group (youth or old adults) should be given priority? Briefly explain your answer.

Respuesta :

Answera and Step-by-step explanation: Correlation Coefficient is the measure of how strong two variables are. There are numerous types of correlation coefficients and the product moment correlation coefficient, also known as Pearson's correlation or Pearson's R is most commonly used in linear regression. The formula to calculate it is:

r = n(∑xy) - (∑x)(∑y) / √[∑x² - (∑x)²].[n∑y² - (∑y)²]

To find the value of R:

1) Separate the values of X and Y and out them in 2 columns.

2) Add 3 more columns: for xy, x² and y²;

3) Find the values of each column;

4) Add each column;

5) Put the sum of each column in its place on the formula above;

6) Find the correlation.

i) For this question, r = 0.9645. As it's positive, means that the two variables are directly linked, i.e., an increase in one variable will produce an increase in the other variable in the same proportion.

ii) The Senator should distribute Norvasc to the old adults groups, because, as the population grows, the death associated with high blood pressure will also grow, as explained by the correlation coefficient.

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