So basically your doing unit rates? Well guess what, I'm studying about that also, and I have a little understanding about unit rates, have you done ratios before?
Answer:
-2 1/5, -1 2/5, 1/5, |-3/5|, |-1 1/5| ,|-2 2/5|
Step-by-step explanation:
Absolute value means take the positive value
-2 1/5
|-1 1/5| = 1 1/5
|-2 2/5| = 2 2/5
1/5
|-3/5| = 3/5
-1 2/5
We want the numbers from smallest to largest
The most negative is
-2 1/5, -1 2/5
Then to the fractions
1/5, |-3/5|
Then the positive numbers
|-1 1/5| ,|-2 2/5|
Answer:
In week 1, 69.15% of sales were 10-inch pizzas, and the remaining 30.85% were 12-inch pizzas; while in week 2, 71.09% of sales were 10-inch pizzas, and the remaining 28.91% were 12-inch pizzas.
Step-by-step explanation:
Given that a takeaway sells 10 inch pizzas and 12 inch pizzas, to determine what proportion sold were 10 inch pizzas in week 1 and what proportion sold were 10 inch in week 2, the following calculation must be performed:
Week 1 = 736 total sales
10-inch pizzas = 509
736 = 100
509 = X
509 x 100/736 = X
50,900 / 736 = X
69.15 = X
100 - 69.15 = 30.85
Thus, in week 1, 69.15% of sales were 10-inch pizzas, while the remaining 30.85% were 12-inch pizzas.
Week 2 = 1076 total sales
10-inch pizzas = 765
1076 = 100
765 = x
765 x 100/1076 = X
76500/1076 = X
71.09 = X
100 - 71.09 = 28.91
Thus, in week 2, 71.09% of sales were 10-inch pizzas, while the remaining 28.91% were 12-inch pizzas.
Answer:
You forgot to put the data
Step-by-step explanation:
Because we don't have the data that represent the responses to the survery I can show you how to can get the mean and the standard deviation.
The mean is the average of the numbers. We use it to get a representative value of the data we are manipulating. We calculate it by adding all the numbers and then divide the sum by how many numbers we have.
The formule we use is:
∑
The standard deviation is a measure of the variation or dispersion of the data we have. A low deviation indicates that our data is few disperced, on the other hand a big deviation indicates a high dispersion of the data.
The formule we use is:
