<h2>Answer: 250 Hamburgers sold</h2><h2>Step-by-step explanation:</h2><h2><u><em>x = hamburgers
</em></u></h2><h2><u><em>y = cheeseburgers
</em></u></h2><h2><u><em>x+y=434
</em></u></h2><h2><u><em>66 fewer cheeseburgers than hamburgers
</em></u></h2><h2><u><em>
</em></u></h2><h2><u><em> </em></u></h2><h2><u><em>y = x - 66
</em></u></h2><h2><u><em>Substitute y into the first equation
</em></u></h2><h2><u><em>x + (x-66) = 434
</em></u></h2><h2><u><em>2x = 434 + 66
</em></u></h2><h2><u><em>2x = 500
</em></u></h2><h2><u><em>x = 250 hamburgers sold</em></u></h2>
169 miles * 5280 ft/ mile = 892320 ft
3 hours * 60 minutes/1 hr = 180 minutes
3 hrs 30 minutes = 180 minutes + 30 minutes = 210 minutes
169 miles/ 3 hrs 30 minutes = 892320 ft/ 210 minutes = 4249.1 ft/ minutes
You write it in verbal expression so 1) 16 less than T is 39 2) product of 2 and w 3) the sum of v and 12 is 30 4) 8 more than w 5) the sum of n and 8 is 47
The method used to collect data for each scenario is observational study , secondary data , simulation .
<h3>What is Data Collection ?</h3>
The accumulation of data to perform research , experiment or any other study is called data collection
It is done by different methods.
While standing in front of the school, Jace recorded the number of students who walked, rode their bikes, took the bus, and were driven there. :
Because all feasible channels and techniques were investigated in order to get accurate data, this study is known as an observational study.
Noah conducted research to learn the data pertaining to the proportion of newborns having brown eyes. Since he didn't perform this directly, it is referred to as secondary data.
Lara repeatedly flipped two coins to see how many times two heads appeared because she knew she had a 25% chance of winning a contest. This is an example of simulation because she wanted to see if she would come up with the same outcome.
To know more about Data Collection
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Outliers are data that are in a very far distance from other values in a set of data
Once an outlier is detected in a set of data, we can do the following to them:
- Discard the outlier
- Change the value of the outlier with another value within close range
- Consider the distribution given
We may have a set of data where some of the <em>values are far in distance from the majority of the data</em>. The set of such data are known as an outlier.
For example, give the set of data;
45 can be considered as an outlier since the <em>distance of data</em><em> to all other data is</em><em> large</em><em>.</em>
Once an outlier is detected in a set of data, we can do the following to them:
- Discard the outlier
- Change the value of the outlier with another value within close range
- Consider the distribution given
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