Answer:
Option C is correct, The scatter plot shows a positive association because y increases as x increases.
Step-by-step explanation:
We are given a graph of scatter plot of points. We need to choose correct option using graph.
Option A: The point (18,2) is an outlier. This point is not shown on graph.
False.
Option B: The scatter plot show linear association. This is not linear association because points are not col-linear.
False
Option C: The scatter plot shows a positive association. This is positive association because y increases as x increases.
True
Option D: The scatter plot shows no association. This is false because it shows positive association.
False
Range is set of all y-values. To find a range of graphed function, we need to know that range starts from the minimum value of graph to maximum value. That's because the minimum value is the least value that you can get by substituting the domain and the maximum value is the largest value that you can get by substituting the domain as well.
Now we don't talk about domain here, we talk about range. See the attachment! You are supposed to focus on y-axis, plane or vertical line. See how the minimum value of function is the negative value while the maximum value is positive.
That means any ranges that don't contain the negative values are cleared out. (Hence A and C choices are wrong.)
Next, range being set of all real numbers mean that graphed functions don't have maximum value or minimum value (We can say that both max and min are infinite.)
Take a look at line graph as an example of range being set of all real numbers, or cubic function.
Answer/Conclusion
- The range exists from negative value which is -9 to the maximum value which is 5.
- That means the range is -9<=y<=5
Is it together or different questions to the reading
Ok, think of 16.4 as 16.40 and 16.5 as 16.50
so between 40 and 50 there are lots of numbers
pick any three
Ex: 16.42, 16.49, 16.45
Answer:
9 days
Step-by-step explanation:
Experimental probability is the number of times an event occurs divided by the total number of trials of the event.
We know the experimental probability, based on past data, that rain will fall 20% chance.
So, one can expect, that in the next 45 days, rain will fall 20% of the days, according to our experimental probability.
First, we find decimal equivalent of 20%. We divide by 100:
20% = 20/100 = 0.2
Now we multiply this with the number of days:
0.2 * 45 = 9
Thus,
One can expect it to rain 9 days
