The conditional relative frequency table was generated using data that compares the number of boys and girls who pack their lunc
h or buy lunch from the cafeteria.
A 4-column table with 3 rows. The first column has no label with entries boys, girls, total. The second column is labeled cafeteria with entries 0.44, 0.4, 0.42. The third column is labeled pack with entries 0.56, 0.6, 0.58. The fourth column is labeled total with entries 1.0, 1.0, 1.0.
35 total girls and 50 total boys were surveyed. How many students bought their lunch from the cafeteria? Round to the nearest whole number.
A 4-column table with 3 rows. The first column has no label with entries boys, girls, total. The second column is labeled cafeteria with entries 0.44, 0.4, 0.42. The third column is labeled pack with entries 0.56, 0.6, 0.58. The fourth column is labeled total with entries 1.0, 1.0, 1.0.
35 total girls and 50 total boys were surveyed. How many students bought their lunch from the cafeteria? Round to the nearest whole number.
2 answers:
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Answer:
After adding 75 the mean and median has increased but mean increased more than median.
Step-by-step explanation:
We have been given a data set: 1, 5, 7, 9, 9, 10. We are asked to find how adding a data point 75 will change the mean and median of our given data set.
Since we know that adding an extreme large data point to a data set increases the mean, while median is less affected by outliers.
Let us find the mean and median of given data set.
Since our data set has 6 data points, so median will be the average of 3rd and 4th data point.
Now let us find mean of new data set after including 75.
Since our new data set will have 7 data points, so median will be the value of middle or 4th data point, that is 9.
We can see that after adding 75 to our data set mean increased from 6.833 to 16.57, while median increased from 8 to 9. Therefore, the mean and median of new data has increased, but mean increased more.