Answer:
54%
Step-by-step explanation:
total animals=27+23=50
9514 1404 393
Answer:
(a, b, c) = (-0.425595, 11.7321, 2.16667)
f(x) = -0.425595x² +11.7321x +2.16667
f(1) ≈ 13.5
Step-by-step explanation:
A suitable tool makes short work of this. Most spreadsheets and graphing calculators will do quadratic regression. All you have to do is enter the data and make use of the appropriate built-in functions.
Desmos will do least-squares fitting of almost any function you want to use as a model. It tells you ...
a = -0.425595
b = 11.7321
c = 2.16667
so
f(x) = -0.425595x² +11.7321x +2.16667
and f(1) ≈ 13.5
_____
<em>Additional comment</em>
Note that a quadratic function doesn't model the data very well if you're trying to extrapolate to times outside the original domain.
we can use MS excel to plot the given data and check whether the graph's trendline has an R-squared of 1. The graph does not fit into a line but fits into an exponential function. The trendline's equation is equal to y = 4e^1.3863x where R squared is equal to 1
Answer:
P(A|D) and P(D|A) from the table above are not equal because P(A|D) = and P(D|A) =
Step-by-step explanation:
Conditional probability is the probability of one event occurring with some relationship to one or more other events
.
P(A|D) is called the "Conditional Probability" of A given D
P(D|A) is called the "Conditional Probability" of D given A
The formula for conditional probability of P(A|D) = P(D∩A)/P(D)
The formula for conditional probability of P(D|A) = P(A∩D)/P(A)
The table
↓ ↓ ↓
: C : D : Total
→ A : 6 : 2 : 8
→ B : 1 : 8 : 9
→Total : 7 : 10 : 17
∵ P(A|D) = P(D∩A)/P(D)
∵ P(D∩A) = 2 ⇒ the common of D and A
- P(D) means total of column D
∵ P(D) = 10
∴ P(A|D) =
∵ P(D|A) = P(A∩D)/P(A)
∵ P(A∩D) = 2 ⇒ the common of A and D
- P(A) means total of row A
∵ P(A) = 8
∴ P(D|A) =
∵ P(A|D) =
∵ P(D|A) =
∵ ≠
∴ P(A|D) and P(D|A) from the table above are not equal
Step-by-step explanation:
