<h2>
Answer with explanation:</h2>
When there is a linear relationship is observed between the variables, we use linear regression predict the relationship between them.
Also, we predict the values for dependent variable by modelling a linear model that best fits the data by drawing a line Y=a+bX, where X is the explanatory variable and Y is the dependent variable.
In other words: The line of best fit is a line through a scatter plot of data points that best describes the relationship between them.
That's why the regression line referred to as the line of best fit.
Answer:
LSA = 532 yds ^2
Step-by-step explanation:
We do not add the triangles in because they are the bases and the bases do not get added in the lateral surface areas.
From left to right
Rectangle 1
A = lw = 9.9 *20 =198
Rectangle 2
A = lw = 6.8 *20 =136
Rectangle 3
A = lw = 9.9 *20 =198
Add them together
198+136+198
532
LSA = 532 yds ^2
The average maximum and minimum values of a formula
Answer:
Step-by-step explanation:
1 table and 2 chairs (2-seat table)
1 table and 4 chairs (4-seat table)
120 people so we need 120 chairs
Some Possibilities :
120 /4 = 30
0( 2-seat table) and 30 (4- seat tables) because 0·2 + 30·4 = 0+120 = 120
2( 2-seat table) and 29 (4- seat tables) because 2·2 + 29·4 = 4+ 116= 120
4( 2-seat table) and 28 (4- seat tables) because 4·2 + 28·4 = 8+ 112= 120
...
120/2 = 60
60( 2-seat table) and 0 (4- seat tables) because 60·2 + 0·4 = 120 + 0 = 120
58( 2-seat table) and 1 (4- seat tables) because 58·2 + 1·4 = 116 + 4 = 120
56( 2-seat table) and 2 (4- seat tables) because 56·2 + 2·4 = 112 + 8 = 120
...
y = 7
Horizontal line, therefore has a slope of zero
