In a recent poll, a random sample of adults in some country (18 years and older) was asked, "When you see an ad emphasizing that a product is 'Made in our country,' are you more likely to buy it, less likely to buy it, or neither more nor less likely to buy it?" The results of the survey, by age group, are presented in the following contingency table. Complete parts (a) through (c).

\begin{tabular}{lccccc}
Purchase likelihood & [tex]$18-34$[/tex] & [tex]$35-44$[/tex] & [tex]$45-54$[/tex] & [tex]$55+$[/tex] & Total \\
\hline
More likely & 207 & 368 & 395 & 408 & 1378 \\
Less likely & 24 & 5 & 25 & 15 & 69 \\
Neither more nor less likely & 297 & 210 & 163 & 108 & 778 \\
\hline
Total & 528 & 583 & 583 & 531 & 2225 \\
\end{tabular}

(a) What is the probability that a randomly selected individual is 45 to 54 years of age, given the individual is more likely to buy a product emphasized as "Made in our country"?

The probability is approximately [tex]$\square$[/tex]
(Round to three decimal places as needed.)

(b) What is the probability that a randomly selected individual is more likely to buy a product emphasized as "Made in our country," given the individual is 45 to 54 years of age?

(c) What is the probability that a randomly selected individual is neither more nor less likely to buy a product emphasized as "Made in our country," given the individual is 18 to 34 years of age?



Answer :

Let's analyze this step-by-step, focusing on the respective probabilities the question asks for:

(a) What is the probability that a randomly selected individual is 45 to 54 years of age, given the individual is more likely to buy a product emphasized as "Made in our country"?

To find this probability, we use the formula for conditional probability:
[tex]\[ P(A | B) = \frac{P(A \cap B)}{P(B)} \][/tex]

Here:
- [tex]\( A \)[/tex] is the event that an individual is 45 to 54 years of age.
- [tex]\( B \)[/tex] is the event that an individual is more likely to buy a product emphasized as "Made in our country".

From the table:
- The number of individuals who are 45 to 54 years of age and more likely to buy the product is [tex]\( 395 \)[/tex].
- The total number of individuals who are more likely to buy the product is [tex]\( 1378 \)[/tex].

Thus,
[tex]\[ P(\text{45 to 54 years} | \text{More likely}) = \frac{395}{1378} \][/tex]

Using our knowledge, the result is approximately:
[tex]\[ \boxed{0.287} \][/tex]

(b) What is the probability that a randomly selected individual is more likely to buy a product emphasized as "Made in our country," given the individual is 45 to 54 years of age?

Again, using the formula for conditional probability:
[tex]\[ P(A | B) = \frac{P(A \cap B)}{P(B)} \][/tex]

Here:
- [tex]\( A \)[/tex] is the event that an individual is more likely to buy the product.
- [tex]\( B \)[/tex] is the event that an individual is 45 to 54 years of age.

From the table:
- The number of individuals who are 45 to 54 years of age and more likely to buy the product is [tex]\( 395 \)[/tex].
- The total number of individuals who are 45 to 54 years of age is [tex]\( 583 \)[/tex].

Thus,
[tex]\[ P(\text{More likely} | \text{45 to 54 years}) = \frac{395}{583} \][/tex]

Using our knowledge, the probability is approximately:
[tex]\[ \boxed{0.678} \][/tex]

With that detailed analysis, we've found the probabilities for both parts (a) and (b) as follows:
- (a) The probability that a randomly selected individual is 45 to 54 years of age, given the individual is more likely to buy a product emphasized as "Made in our country" is approximately [tex]\( \boxed{0.287} \)[/tex].
- (b) The probability that a randomly selected individual is more likely to buy a product emphasized as "Made in our country," given the individual is 45 to 54 years of age is approximately [tex]\( \boxed{0.678} \)[/tex].