I have to solve this inequality and then graph the solution
1 answer:
9514 1404 393
Answer:
-8 < r ≤ 3
Step-by-step explanation:
Divide by the coefficient of r. It is negative, so the comparisons will be reversed.
24/-3 < r ≤ -9/-3
-8 < r ≤ 3
The < has no "or equal to" as a part of it, so the number -8 is not in the solution set. There will be an open circle on the graph at that point.
The ≤ includes the "or equal to" case, so the number 3 is in the solution set. There will be a solid dot on the graph at that point.
The line is shaded between the two dots, because values in between -8 and 3 are part of the solution set.
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B) The x-intercept indicates all tickets will be sold within 30 minutes
Step-by-step explanation:
From the equation of the function
f(x) = 200 -5x
The domain of f(x) is [0,40] for values of x that are true and the range is [0,200] for values of y from corresponding values of x
The constant 200, is the y-intercept which indicates that at the starting time of selling the tickets, 200 tickets were available
The slope, -5 indicates that the tickets were being sold at a rate of 5 tickets per minute. This shows that in 40 minutes,the 200 tickets will be sold out.
Learn More
To interpret linear functions:brainly.com/question/13599312
Keywords ;theater, ticket, inventory, movie, modeled, function, minutes, elapse, graph, domain, statement, false
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Answer:
It is a good Estimator of the Population Mean because the distribution of the sample midrange is just same as the distribution of the random variable.
Step-by-step explanation: from the table,
Minimum value = 34
maximum values = 1084
The sample mid-range can be computed as:
(Min.value + max.value)/2
(34 + 1084)/2
Sample mid-range = 55
The sample midrange uses only a small portion of the data, but can be heavily affected by outliers.
It provides information about the skewness and heavy-tailedness of the distribution which is just same as the distribution of the random variable.
The nature of this distribution is not intuitive but the Central Limit in which it will approach a normal distribution for large sample size.
