Data Interpretation Questions: Work Order

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 "") The Johnson family tracked its monthly grocery budget for October and November. How much more money did the the Johnson family spend on meat in October than on desserts in November?
Incorrect. [[snippet]] The difference in percentage of the budget spent on meat and desserts is about 28%. However, different total amounts were spent in October and November, so you should convert the percents to dollar amounts first.
Incorrect. [[snippet]] The amount of money the family spends on desserts in November is $80. Find the amount spent on meat in October, then find the difference between these two values.
Incorrect. [[snippet]] The total money spent on meat in October is $206. If this were the correct choice, then the family would have spent $0 on desserts in November, which you can see from the graph is not the case.
Correct. If you look at the question first, you know that it is asking for a difference in money spent, so you should look for these labels on the graph. Unfortunately, the graph is labeled in percentages, and the total amount spent each month is different, so you will need to convert the appropriate percents to dollar amounts before you take the difference. From the graph, you can __Ballpark__ the percentage of the November budget spent on dessert was about 10% of the total budget. You calculate that 10% of $710 is $71. You can also __Ballpark__ the percentage of the October spent on meat as about 33% of the total budget, and 33% of $600 is $200. $$\displaystyle \$200 - \$71 = \$129$$ By far the closest choice to your estimated $129 is $126. The other answers are so far off that you can be confident your __Ballparking__ got you the right answer.
Incorrect. [[snippet]] The difference between the total budgets in October and November is $110.
$28
$80
$110
$126
$206

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