Answer:
Cost of five blouses = $145
Step-by-step explanation:
Let
x = cost of blouse
y = cost of skirt
15x + 2y = 505 (1)
5x + 2y = 215 (2)
Subtract (2) from (1) to eliminate y
15x - 5x = 505 - 215
10x = 290
x = 290/10
x = 29
Substitute x = 29 into (2)
5x + 2y = 215 (2)
5(29) + 2y = 215
145 + 2y = 215
2y = 215 - 145
2y = 70
y = 70/2
y = 35
x = cost of blouse = $29
y = cost of skirt = $35
How much do 5 such blouses cost?
cost of a blouse = $29
Cost of five blouses = $29 × 5
= $145
Cost of five blouses = $145
Answer:
umm what do you mean can like you explain
Answer:
0<x<12
Step-by-step explanation:
These signs < should have a line under it btw
15 days because if it’s 1/5 a day then in 5 days it’ll be 5/5 times 3 which is 15 days
Answer:
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
Step-by-step explanation:
We are given a linear regression model that relates daily high temperature, in degrees Fahrenheit and number of lemonade cups sold.

Where y is the number of cups sold and x is the daily temperature in Fahrenheit.
Residual value:
A residual value basically shows the position of a data point with respect to the regression line.
A residual value of 0 is desired which means that the regression line best fits the data.
The Residual value is calculated by
Residual = Observed value - Predicted value
The predicted value of number of lemonade cups is obtained as

So the predicted value of number of lemonade cups is 23 and the observed value is 21 so the residual value is
Residual = Observed value - Predicted value
Residual = 21 - 23
Residual = -2
The negative residual value indicates that the data point lies below the regression line.