The perpetual inventory system is an inventory management method that records when stock is sold or received in real-time.
<h3>
How to depict thejournal?</h3>
a. Debit Accounts Receivable 12000
Credit Sales 12000
Debit Cost of Merchandise Sold 6500
Credit Merchandise Inventory 6500
b. Debit Cash 9500
Credit Sales 9500
Debit Cost of Merchandise Sold 5300
Credit Merchandise Inventory 5300
c. Debit Cash 2900
Credit Sales 2900
Debit Cost of Merchandise Sold 1700
Credit Merchandise Inventory 1700
d. Debit Credit Card Expense 385
Credit Cash 385
e. Debit Credit Card Expense 75
Credit Cash 75
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Given:
The objective is to find the slope of the straight line.
Explanation:
The general equation to find the slope is,
Let's consider two coordinates from the graph.
On plugging the values in the equation of slope,
Hence, the slope of the straight line is -5.
The lateral area of the prism is given by:
LA=[area of the two triangles]+[area of the lateral rectangles]
hypotenuse of the triangle will be given by Pythagorean:
c^2=a^2+b^2
c^2=6^2+4^2
c^2=52
c=sqrt52
c=7.211'
thus the lateral area will be:
L.A=2[1/2*4*6]+[6*8]+[8*7.211]
L.A=24+48+57.69
L.A=129.69 in^2
The total are will be given by:
T.A=L.A+base area
base area=length*width
=4*8
=32 in^2
thus;
T.A=32+129.69
T.A=161.69 in^2
Hope this helps:) plz mark brainiest i would really apperciate it
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The equation which is equivalent to 
is 
or x = 6 (
).
<u>Step-by-step explanation:</u>
Given Equation:
As we know, in terms of logarithmic rules, when b is raised to the power of y is equal x:
Then, the base b logarithm of x is equal to y
Now, use the logarithmic rule for the given equation by comparing with above equation. We get b = x, y = 2, and x = 36. Apply this in equation,
When taking out the squares on both sides, we get x = 6. Hence, the given equation can be written as
Answer:
Below are the responses to the given question:
Step-by-step explanation:
Let X become the random marble variable & g have been any function.
Now.
For point a:
When X is discreet, the g(X) expectation is defined as follows
Then there will be a change of position.
E[g(X)] = X x∈X g(x)f(x)
If f is X and X's mass likelihood function support X.
For point b:
When X is continuing the g(X) expectations is calculated as, E[g(X)] = Z ∞ −∞ g(x)f(x) dx, where f is the X transportation distances of probability.If E(X) = −∞ or E(X) = ∞ (i.e., E(|X|) = ∞), they say it has nothing to expect from EX is occasionally written to stress that a specific probability distribution X is expected.Its expectation is given in the form of,E[g(X)] = Z x −∞ g(x) dF(x). , sometimes for the continuous random vary (x). Here F(x) is X's distributed feature. The anticipation operator bears the lineage of comprehensive & integral features. The superposition principle shows in detail how expectation maintains equality and is a skill.
