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vova2212 [387]
3 years ago
7

What is 12 over three equals four over one

Mathematics
2 answers:
Phoenix [80]3 years ago
4 0
<h2><em>It's exactly what it says. 12/3 = 4. 4/1 = 4. Thus, 4 = 4. It's already solved.</em></h2>
pochemuha3 years ago
3 0

\text{Hey there!}

\mathsf{\dfrac{12}{3}=\dfrac{4}{1}\ true\ or\ false \ ?}

\text{The answer is\ \bf{TRUE}}

\mathsf{\dfrac{12\div3}{3\div3}}\\\\\mathsf{12\div3=4}\\\\\mathsf{3\div3=1}\\\\\mathsf{Which\ convets\ to: \dfrac{4}{1}}

\boxed{\boxed{\mathsf{Thus,\ this\ makes\ your\ answer\ \boxed{\mathsf{TRUE\ because\ they\ both\ equal\ 4}}}}}\checkmark

\text{Good luck on your assignment and enjoy your day!}

~\dfrac{\frak{LoveYourselfFIrst}}{:)}

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A bacteria culture begins with 15 bacteria which double in amount at the end of every hour. How many bacteria are grown during t
Eva8 [605]
The answer is 30720

A = P * rⁿ
A - the final population
r - the growth rate
P - the initial number of bacteria
n - the number of hours

We know:
A = ?
r = 2 (it doubles)
P = 15
n = 12

After 11 hours
A(11) = 15 * 2¹²
A(11) = 15 * 2048
A(11) = 30720

After 12 hours
A(12) = 15 * 2¹²
A(12) = 15 * 4096
A(12) = 61440

<span>How many bacteria are grown during the 12th hour?
A(12) - A(11) = 61440 - 30720 = 30720</span>
8 0
3 years ago
Pls help... again
Rashid [163]

Answer:

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9x^ - 30x - 25

.............................

4 0
3 years ago
Read 2 more answers
Need help with this question please somebody help me
Leokris [45]

Answer:

$138.95

Step-by-step explanation:

Since Maloney picked 1985 apples he falls in the payscale of 0.07 per apple.

Thus 1985 * .07 = 138.95

7 0
2 years ago
A data mining routine has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so) an
chubhunter [2.5K]

Answer:

The classification matrix is attached below

Part a

The classification error rate for the records those are truly fraudulent is 65.91%.

Part b

The classification error rate for records that are truly non-fraudulent is 96.64%

Step-by-step explanation:

The classification matrix is obtained as shown below:

The transaction dataset has 30 fraudulent correctly classified records out of 88 records, that is, 30 records are correctly predicted given that an instance is negative.

Also, there would be 88 - 30 = 58 non-fraudulent incorrectly classified records, that is, 58 records are incorrectly predicted given that an instance is positive.

The transaction dataset has 920 non-fraudulent correctly classified records out of 952 records, that is, 920 records are correctly predicted given that an instance is positive.

Also, there would be 952 - 920 = 32 fraudulent incorrectly classified records, that is, 32 records incorrectly predicted given that an instance is negative.

That is,

                                                                            Predicted value

                           Active value                 Fraudulent       Non-fraudulent

                              Fraudlent                         30                       58

                          non-fraudulent                   32                     920

The classification matrix is obtained by using the information related to the transaction data, which is classified into fraudulent records and non-fraudulent records.

The error rate is obtained as shown below:

The error rate is obtained by taking the ratio of \left( {b + c} \right)(b+c) and the total number of records.

The classification matrix is, shown above

The total number of records is, 30 + 58 + 32 + 920 = 1,040

The error rate is,

\begin{array}{c}\\{\rm{Error}}\,{\rm{rate}} = \frac{{b + c}}{{{\rm{Total}}}}\\\\ = \frac{{58 + 32}}{{1,040}}\\\\ = \frac{{90}}{{1,040}}\\\\ = 0.0865\\\end{array}  

The percentage is 0.0865 \times 100 = 8.65

(a)

The classification error rate for the records those are truly fraudulent is obtained by taking the rate ratio of b and \left( {a + b} \right)(a+b) .

The classification error rate for the records those are truly fraudulent is obtained as shown below:

The classification matrix is, shown above and in the attachment

The error rate for truly fraudulent is,

\begin{array}{c}\\FP = \frac{b}{{a + b}}\\\\ = \frac{{58}}{{30 + 58}}\\\\ = \frac{{58}}{{88}}\\\\ = 0.6591\\\end{array}  

The percentage is, 0.6591 \times 100 = 65.91

(b)

The classification error rate for records that are truly non-fraudulent is obtained by taking the ratio of d and \left( {c + d} \right)(c+d) .

The classification error rate for records that are truly non-fraudulent is obtained as shown below:

The classification matrix is, shown in the attachment

The error rate for truly non-fraudulent is,

\begin{array}{c}\\TP = \frac{d}{{c + d}}\\\\ = \frac{{920}}{{32 + 920}}\\\\ = \frac{{920}}{{952}}\\\\ = 0.9664\\\end{array}

The percentage is, 0.9664 \times 100 = 96.64

8 0
3 years ago
Joe spent 1 1/3 hours studying for his math test. Randy studied for the amount of time that Joe did. What fraction of a hour did
PSYCHO15rus [73]

Answer:

1 1/3

Step-by-step explanation:

Randy studied for the same amount of time so it would be the same answer im not sure if I'm correct but hope this helps

7 0
3 years ago
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