Categorical data may or may not have some logical order
while the values of a quantitative variable can be ordered and
measured.
Categorical data examples are: race, sex, age group, and
educational level
Quantitative data examples are: heights of players on a
football team; number of cars in each row of a parking lot
a) Colors of phone cover - quantitative
b) Weight of different phones - quantitative
c) Types of dogs - categorical
d) Temperatures in the U.S. cities - quantitative
0^9 +7x+189yx−3y
o
9
+7x−3y
9
+7x+3y
9
−7x−3y
9
−7x+3y
9
+7x+189yx−3y
2 Collect like terms.
{o}^{9}+(7x+7x-7x-7x+7x)+(-3{y}^{9}+3{y}^{9}-3{y}^{9}+3{y}^{9})+189yx-3y
o
9
+(7x+7x−7x−7x+7x)+(−3y
9
+3y
9
−3y
9
+3y
9
)+189yx−3y
3 Simplify.
{o}^{9}+7x+189yx-3y
o
9
+7x+189yx−3y
Answer
z11.7 is between 1 and 2 standard deviations of the mean.
Step-by-step explanation:
Answer:
I don't know if it's correct
but I tried
Step-by-step explanation:
let the angle be x
20+4x+x=180
20+5x=180
5x=160
x=32
Factoring may be the easiest one
