Answer:
JK≅MN, KL≅NO and ∠K≅∠N
Step-by-step explanation:
we know that
A Reflection is a transformation that doesn't change the size or shape of the figure
so
Triangle JKL and triangle MNO are congruent
The corresponding sides and the corresponding angles are congruent
therefore
JK≅MN, KL≅NO,JL≅MO
and
∠J≅∠M, ∠K≅∠N,∠L≅∠O
Answer:
6
Step-by-step explanation:
First subtract the fixed fee. 59-5=54
Divide 54 by 9.
6
Answer:
See below.
Step-by-step explanation:
Recall that the x-intercept is basically: (x,0).
In other words, we just need to substitute y with 0 in order to find the x-intercept.
Thus, we will have:
Let the first number be 'x' and the second number is 'y'
Equation 1: x + y = 52
Equation 2: x - y = 38
Rearranging equation 2 to make either x or y the subject
x = 38 + y
Substituting x = 38 + y into equation 1
x + y = 52
(38+y) + y = 52
38 + 2y = 52
2y = 52 - 38
2y = 14
y = 7
Substitute y = 7 into either equation 1 or equation 2 to find x
x + y = 52
x + 7 = 52
x = 52 - 7
x = 45
x = 45
y = 7
Answer:
Methods of obtaining a sample of 600 employees from the 4,700 workforce:
Part A: The type of sampling method proposed by the CEO is Convenience Sampling.
Part B: When there are equal number of participants in both campuses, stratification by campus would give a more precise approximation of the proportion of employees who are satisfied with the cleanliness of the breakrooms than stratification by gender. Another method to ensure that stratification by campus gives a more precise approximation of the proportion of employees who are satisfied with the cleanliness of the breakrooms than stratification by gender is to ensure that the sample is proportional to the proportion of each campus to the whole population or workforce.
Step-by-step explanation:
A Convenience Sampling technique is a non-probability (non-random) sampling method and the participants are selected based on availability (early attendees). The early attendees might be different from the late attendees in characteristics such as age, sex, etc. Therefore, sampling biases are present. All non-probability sampling methods are prone to volunteer bias.
Stratified sampling is more accurate and representative of the population. It reduces sampling bias. The difficulty arises in choosing the characteristic to stratify by.
