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movie theater a movie theater is tracking the number of movie tickets a…

Question

movie theater a movie theater is tracking the number of movie tickets and bags of popcorn sold each week.

is there a correlation between the variables in the data? is there likely causation?

a) correlation but no causation

b) positive correlation and causation

c) negative correlation and causation

d) neither correlation nor causation

Explanation:

Step1: Analyze the data trend

Looking at the number of tickets sold (332, 401, 275, 353, 411) and bags of popcorn sold (145, 202, 103, 151, 197). When tickets sold increase (e.g., from week 1 to week 2: 332→401), popcorn sold also increases (145→202). When tickets sold decrease (week 2 to week 3: 401→275), popcorn sold also decreases (202→103). There is a general pattern of movement together, indicating a correlation.

Step2: Check for causation

Causation would mean that one variable directly causes the other. Here, more people buying tickets (more movie - goers) likely leads to more popcorn sales as movie - goers often buy popcorn. But it's not a strict causation (e.g., a person could buy a ticket and not popcorn). However, the positive trend in both variables' movement (when one is up, the other is up; when one is down, the other is down) shows a positive correlation. And there is a reasonable causal link (more movie - goers→more potential popcorn buyers).

Answer:

B. positive correlation and causation