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<em>It's nice of you to offer, but no thanks.</em>
To correctly graph this, you need to set up a simple equation and table of values. Luckily, this equation is dead-simple; I'll define <em>y</em> as the total cost and <em>x</em> as the number of water bottles sold.
Since 1.50$ is the cost for one bottle, multiplying that with your variable that defined the amount of bottles, <em>x</em>, gets you the total, <em>y</em>. Now that we have a basic equation, we can begin plugging in values.
Recall that a function is basically just something that takes in a value and returns another one; in our case, it takes the <em>amount of bottles</em> and returns the <em>total cost. </em>Now, plug in the x-values present on the graph (specifically only whole numbers, since you can't have a half bottle). I can't make a proper table but I'll make do.
x y
--------
0 0
1 1.5
2 3
3 4.5
4 6
5 7.5
-----------
Great, now that you have a table of values all you have to do is plug them into the graph, which I've attached. It's pretty crude since I drew it in mspaint but I'm sure you get the point at this point.
Answer:
46.18% of the items will weigh between 6.4 and 8.9 ounces.
Step-by-step explanation:
We are given that the weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces.
<em>Let X = weight of items produced by a machine</em>
The z-score probability distribution for is given by;
Z = ~ N(0,1)
where, = mean weight = 8 ounces
= standard deviation = 2 ounces
The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X.
So, percentage of items that will weigh between 6.4 and 8.9 ounces is given by = P(6.4 < X < 8.9) = P(X < 8.9 ounces) - P(X 6.4 ounces)
P(X < 8.9) = P( <
) = P(Z < 0.45) = 0.67364 {using z table}
P(X 70) = P(
) = P(Z
-0.80) = 1 - P(Z < 0.80)
= 1 - 0.78814 = 0.21186
<em>Now, in the z table the P(Z </em><em> x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 0.45 and x = 0.80 in the z table which has an area of </em>0.67364<em> and </em>0.78814<em> respectively.</em>
Therefore, P(6.4 < X < 8.9) = 0.67364 - 0.21186 = 0.4618 or 46.18%
<em>Hence, 46.18% of the items will weigh between 6.4 and 8.9 ounces.</em>