I think the correct answer would be B. If the residuals for brand A form an increasing curve, and the residuals for brand B form a U-shaped pattern, then neither of the data is likely to be linear. In order to be linear, the residuals of both data set should be, more or less, linear or approaching linearity in nature. Therefore, the linear regression that was done would not give good results since it is only applicable to linear data sets. Also, you can say that the relation of the data sets of the products are not linear. It would be best to do a curve fitting for both sets by using different functions like parabolic functions.
Yes, ∠1 and ∠2 are the remote interior angles of ∠5, but ∠3 is not.
You're looking for the remote interior angles, so while ∠3 has a measure that when added to ∠5 = 180°, it is adjacent to ∠5 so it is not remote from it.
The perimeter doesn't tell you the area, and neither of them
can be calculated by knowing the other one.
Check this out:
Dimensions Perimeter Area .
1 by 38 78 38 square feet
2 by 37 78 74 square feet
3 by 36 78 108 square feet
5 by 34 78 170 square feet
10 by 29 78 290 square feet
15 by 24 78 360 square feet
17 by 22 78 374 square feet
19 by 20 78 380 square feet
19.5 by 19.5 78 380.25 square feet
Nine same perimeters, nine different areas !
Here's one more ... a long skinny one:
1 inch by 38ft 11in Perimeter = 78 ft. Area = 3.24 square feet.
Answer:
A. x = 11√3
B. y = 11
Step-by-step explanation:
A. Determination of the value of x.
Angle θ = 60°
Hypothenus = 22
Opposite = x =?
We can obtain the value of x by using sine ratio as illustrated below:
Sine θ = Opposite / Hypothenus
Sine 60 = x / 22
√3/2 = x / 22
Cross multiply
2 * x = 22√3
Divide both side by 2
x = (22√3) / 2
x = 11√3
B. Determination of the value of y.
Angle θ = 60°
Hypothenus = 22
Adjacent = y =?
We can obtain the value of y by using cosine ratio as illustrated below:
Cos θ = Adjacent / Hypothenus
Cos 60 = y / 22
½ = y / 22
Cross multiply
y = ½ × 22
y = 11
Answer:
P(POSc/Sc)
Step-by-step explanation:
As,
POS= Test has positive results
and
S=Adult has tuberculosis.
The test correctly identifies 74.6% of the time adults with a tuberculosis and correctly identifies those without tuberculosis 76.53% of the time.
In the above statement 76.53% describes the probability of adult who don't have tuberculosis gets the negative results as test is correctly identifying.
So, getting negative results means that not positive results and for this event the notation of complement POSc is used. Also, not having tuberculosis can be denoted as Sc. So,
POSc= Test has negative results
Sc=Adult hasn't tuberculosis
Thus, P(POSc/Sc) depicts the probability of adults not having tuberculosis gets correct results.
Hence, P(POSc/Sc)=76.53%
