Answer:
The solution set is the empty set.
Step-by-step explanation:
{x | x < 2} is the set of all numbers less than 2. This means x can take values such as 1.99, 0, -2000 and so on. That is, all values less than 2.
{x | x ≥ 2} is the set of all numbers equal to or greater than 2. This means x can take values such as 2, 2.1, 5000, and so on. That is, 2 or any value greater than 2.
Since there is no sign between the two sets, the question is asking for the intersection between these two sets. That is, what elements are common to these two sets? As we can see, the two sets don't have any common element. Hence, their intersection is the empty set.
(Note that the union of these two sets would be the set of all real numbers as that includes all elements from either set).
Answer:
the set containing all objects or elements and of which all other sets are subsets.
Step-by-step explanation:
Answer:
StartFraction negative 1 Over k cubed EndFraction
Step-by-step explanation:
3k / (k + 1) × (k²- 1) / 3k³
= 3k(k² - 1) / (k + 1)(3k³)
= 3k³ - 3k / 3k⁴ + 3k³
= -3k / 3k⁴
= -1/k³
StartFraction k + 1 Over k squared EndFraction
(k + 1) / k²
StartFraction k minus 1 Over k squared EndFraction
(k - 1)/k²
StartFraction negative 1 Over k cubed EndFraction
= -1/k³
StartFraction 1 Over k EndFraction
= 1/k
Answer: 1,2 and 4
Step-by-step explanation:
factors of 12 are : 1,2,3,4,6,12
factors of 28 are :1,2,4,7,14,28
commom factors are= 1,2,4
Answer:
Option a) u is called the "error term". It is the error we make in prediction
Option d) x is called the independent variable because x is independent from y and u.
Step-by-step explanation:
We are given the following information in the question:

where y is the dependent variable, x is the independent variable.
: It is the value of y when x is zero, that is y-intercept.
: It is the coefficient of x in predicting the dependent variable y.
u is the error term.
- An error term represents the margin of error.
- It refers to the sum of the deviations within the regression line, that is the difference between the predicted value and the observed value of y.
Thus, Option A) u is the error term and Option D) x is called the independent variable because x is independent from y and u are the correct answer.