Answer:
9 cherry, 6 blueberry
Step-by-step explanation:
lets do a table!
cherry | blueberry
----------------------------
3 2
6 4
9 6
When there are 2 blueberry, there are 3 cherry. 3 is 1 more than 2. When there are 4 blueberry, there are 6 cherry. 6 is 2 more than 4. When there are 6 blueberry, there aare 9 cherry. 9 is 3 more than 6.
Answer:
Your answer is: No solution
Step-by-step explanation:
Hope this helped : )
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Answer:
Step-by-step explanation:
Let
n -----> number of tickets
C ----> represent the cost of buy n tickets online
we have the ordered pairs
(1,16.50) and (2,30.50)
<em>Find out the slope of the linear equation</em>
The formula to calculate the slope between two points is equal to
substitute the values
<em>Find the equation of the line in slope intercept form</em>
we have
substitute
substitute
The domain of the function is all positive integers (whole numbers) including zero
{0,1,2,3,4,...}
Answer:
18. 46
19. 0.7
22. 4 3/4
23. 54.5
26. 14
27. 11.5
31. 15
etc.
Step-by-step explanation:
absolute value means that the sign in front of the # doesn't matter, you just have to look at the positive value, for example:
absolute value of 46 = 46
absolute value of - 36 = 36
(imagine the sign in front of the # isn't there)
Answer:
Option B - False
Step-by-step explanation:
Critical value is a point beyond which we normally reject the null hypothesis. Whereas, P-value is defined as the probability to the right of respective statistic which could either be Z, T or chi. Now, the benefit of using p-value is that it calculates a probability estimate which we will be able to test at any level of significance by comparing the probability directly with the significance level.
For example, let's assume that the Z-value for a particular experiment is 1.67, which will be greater than the critical value at 5% which will be 1.64. Thus, if we want to check for a different significance level of 1%, we will need to calculate a new critical value.
Whereas, if we calculate the p-value for say 1.67, it will give a value of about 0.047. This p-value can be used to reject the hypothesis at 5% significance level since 0.047 < 0.05. But with a significance level of 1%, the hypothesis can be accepted since 0.047 > 0.01.
Thus, it's clear critical values are different from P-values and they can't be used interchangeably.