Colfax:
Add the ratio numbers together:
5 + 4 = 9
Divide total students by that:
270 / 9 = 30
Multiply each ratio by 30:
Boys = 30 *5 = 150
Girls = 30 * 4 = 120
Do the same for Winthrop:
4 +5 = 9
180 /9 = 20
Boys = 20 * 4 = 80
Girls = 20 * 5 = 100
Total students = 270 + 180 = 450
Total Girls = 120 + 100 = 220
Fraction that are girls = 220 / 450 which reduces to 22/45
Answer:
Step-by-step explanation:
The scale factor (C) is the ratio of corresponding parts of the two pyramids.
The ratio of the areas is the square of the scale factor.
Answer:
$1.75
Step-by-step explanation:
The selling for each candy bar may be determined by a set of linear equations. This pair of linear equations may be solved simultaneously by using the elimination method. This will involve ensuring that the coefficient of one of the unknown variables is the same in both equations.
It may be solved by substitution in that one of the variable is made the subject of the equation and the result is substituted into the second equation
.
Let the cost of a snack bag be s and that of a candy bar be c, then if on Wednesday the students or 23 snack bags and 36 candy bars that raised $114.75 on Thursday the seventh so 37 snack bags and 36 candy bars that raised $146.25
23s + 36c = 114.75
37s + 36c = 146.25
14s = 31.5
s = $2.25
23(2.25) + 36c = 114.75
36c = 114.75 - 51.75
36c = 63
c = 63/36
= $1.75
Complete question is;
Regarding the violation of multicollinearity, which of the following description is wrong?
a. It changes the intercept of the regression line.
b. It changes the sign of the slope.
c. It changes the slope of the regression line.
d. It changes the value of F-tests.
e. It changes the value of T-tests
Answer:
a. It changes the intercept of the regression line
Step-by-step explanation:
Multicollinearity is a term used in multiple regression analysis to show a high correlation between independent variables of a study.
Since it deals with independent variables correlation, it means it must be found before getting the regression equation.
Now, looking at the options, the one that doesn't relate with multicollinearity is option A because the intercept of the regression line is the value of y that is predicted when x is 0. Meanwhile, multicollinearity from definition above does in no way change the intercept of the regression line because it doesn't predict the y-value when x is zero.
