Answer:
4 miles/1 day=56 miles/X days
X=56/4=14
Step-by-step explanation:
Answer:
Step-by-step explanation:
with the numbers that come out of result
Answer:
- <em>The net change in how many bags are on the shelf, from the beginning of Tuesday to the end of Monday is -</em><u>2.</u>
Explanation:
The change in the number of bags any day is the number of bags is equal to the number of bags purchased to restock less the number of bags sold that day.
- Change = bags purchased to restock - bags sold
At the end of <em>Tuesday</em>, the change is:
- Change: 6 - 5 = 1 (note that this means that the number of bags increases by 1)
At the end of <em>Wednesday</em>, the change is:
- Change: 12 - 8 = 4 (the number of bags increases by 4)
At the end of <em>Thursday</em>, the change is:
- Change: 12 - 2 = 10 (the number of bags increases by 10)
At the end of <em>Friday</em>, the change is:
- Change: 18 - 19 = - 1 (the number of bags decreases by 1).
At the end of <em>Saturday</em>, the change is:
- Change: 24 - 22 = 2 (the number of bags increases by 2).
At the end of <em>Sunday</em>, the change is:
- Change: 0 - 15 = - 15 (the number of bags decreases by 15).
At the end of <u>Monday</u>, the change is:
- Change: 0 - 3 = - 3 (the number of bags decreases by 3).
The net change in how many bags are on the shelf, from the beginning of Tuesday to the end of Monday equals the algebraic sum of every change:
- Net change = 1 + 4 + 10 + (-1) + 2 + (-15) + (-3)
- Using associative property: (1 + 4 + 10 + 2) - (1 + 15 +3)
- Simplifying: 17 - 19 = -2
<u>Conclusion</u>: the net change in how many bags are on the shelf, from the beginning of Tuesday to the end of Monday is -2, meaning that the number of bags, after taking into account all sales and restock, decreases by 2.
Answer: A. 0.62
Step-by-step explanation:
As all the given r values are positive therefore, there is a positive correlation.
A positive correlation means that if one variable gets bigger, the other variable tends to get bigger.
The strongest linear relation is stipulated by a correlation coefficient 'r' of -1 or 1.
The weakest linear relation is stipulated by a correlation coefficient equal to 0.
Thus, the nearest number to 1 , represents the strongest correlation.
Therefore, A. 0.62 is the required answer which represents the strongest correlation. .
Answer:
The statement which could explain the effect of confounding is:
Because the weather was generally better this year compared to last year, the attendance may have increased.
Step-by-step explanation:
A confounding variable has some effect on the dependent variable. Confounding variables are the variable(s) that are additional to the independent and dependent variables in an experiment. Since the presence of confounding variables affect the variables being studied so that the results do not reflect the actual relationship, it is best to exclude or control them through randomization, restriction, and matching.
