The graphed function, F(x), has a value greater than 0 over the intervals (-0.7, 0.76) and (0.76, ∞) . F(x) > 0 over the intervals (-0.7, 0.76) and (0.76, ∞) is the correct statement [Fourth choice].
About a Graphed Function
The function graph of an object F stands for the set of all points in the plane that are (x, f(x)). The graph of f is also known as the graph of y = f. (x). The graph of an equation is thus a specific example of the graph of a function. A graphed function is a function that has been drawn out on a graph.
It is evident from the attached graph that the supplied function exceeds 0 for the following range:
-0.7 < F(x) < 0.76
And, 0.76 < F(x) < ∞
As a result, the intervals for which the given graphed function, F(x) is greater than 0 are as follows,
(-0.7, 0.76) and (0.76, ∞)
Learn more about a graphed function here:
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Answer:
initial value=2
rate of change=1
Step-by-step explanation:
rate of change=(3-2)/(1-0)=1
Answer: Yes
Explanation:
120 % = 1.2
If Maxine is correct, then she spent 1.2
times the hours she did homework than last week.
15 ⋅ 1.2 = 18.0 = 18
15 hours ⋅ 1.2 = 18.0 hours = 18 hours
Maxine is correct
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❖ The 3 remains the same when 9,321 is rounded because if you look to the right of the number in the hundreds place, you see 2. 5 and above, give it a shove (round up). 4 and below, leave it alone (round down). Since 2 is below 5, we leave it alone. So 9,321 is rounded to 9,300.
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Answer:
And we can find the individual probabilities like this:
And adding we got:
Step-by-step explanation:
Previous concepts
The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".
Let X the random variable of interest, on this case we now that:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
Solution to the problem
For this case we want to find this probability:
And we can find the individual probabilities like this:
And adding we got:
