A small business owner has created a linear regression model to predict the number of new customers who will visit a shop based
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Answers:
Lower bound = 41.3
Upper bound = 41.5
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Explanation:
49.15 is the smallest f can be while 49.24 is the largest it can be. Well technically we could have something like 49.2499 or 49.24999 and so on. We slowly approach 49.25 but never actually get there
So the variable f is between 49.15 and 49.25 inclusive of the first value but excluding the second value. We can write it as
For similar reasoning,
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If we wanted to subtract those variables and get the smallest result possible, then we need to pick values that are closest together. It might help to set up a number line.
This means we'd go for f = 49.15 and g = 7.85
The lower bound for f-g is f-g = 49.15-7.85 = 41.3
In contrast, the upper bound is when the two variables are spaced as far apart as possible. The upper bound is f-g = 49.25 - 7.75 = 41.5