Answer:
.98
Step-by-step explanation:
1-(35/43)^18 im in stats too tehee
I will rewrite the question for better understanding:
Ashley recently opened a store that uses only natural ingredients. She wants to advertise her products by distributing bags of samples in her neighborhood. It takes Ashley 2/3 of a minute to prepare one bag. It takes each of her friends 75% longer to prepare a bag. How many hours will it take Ashley and 4 of her friends to prepare 1575 bags of samples?
Answer:
- <em><u>5.3 hours</u></em>
Explanation:
<u>1) Time it takes Ashley to preprate one bag: </u>
<u>2) Time it takes each friend of Ashley: 75% more than 2/3 min</u>
- 75% × 2/3 min = 0.75 × 2/3 min = 3/4 × 2/3 min= 2/4 min = 1/2 min = 0.5 min
- 2/3 min + 1/2 min = 7/6 min
<u>3) Time it takes Ashley and the 4 friends working along to prepare one bag:</u>
- Convert each time into a rate, since you can set that the total rate of Ashley along with her four friends is equal to the sum of each rate:
- Rate of Ashley: 1 bag / (2/3) min = 3/2 bag/min
- Rate of each friend: 1 bag / (7/6) min = 6/7 bag/min
- Rate of Ashley and 4 friends = 3/2 bag/min + 4 × 6/7 bag/min = (3/2 +24/7) bag/min = 69/14 bag/min
<u>4) Time of prepare 1575 bags of samples:</u>
- time = number of bags / number of bags per min = 1,575 bags / (69/14) bags/min = 319.56 min
<u>5) Convert minutes to hours:</u>
- 356.56 min × 1 hour / 60 min = 5.3 hours
Answer:
The number of textbooks of each type were sold is <u>134 math </u>and <u>268 psychology </u>books.
Step-by-step explanation:
Given:
Total number of math and psychology textbooks sold in a week is 402.
Now, let the number of math textbooks sold be
.
And, the number of psychology textbooks be
.
According to question:


Dividing both sides by 3 we get:

So, total number of math textbooks were 134 .
And, total number of psychology textbooks were 
.
Therefore, the number of textbooks of each type were sold is 134 math and 268 psychology books.
Answer:
Step-by-step explanation:
The best option is for the consultant to remove these data points because they are outliers. Unusual data points which are located far from rest of the data points are known as outliers.