How many 1/6 cups of raisins are in 3/2 cups of raisins?

Jordan can clean 57 houses a week. Taylor can clean 27 houses in 3 days. If they work together, how many days

kirill [66]

7.29 but if you have to round up, 8 days

7 0

2 years ago

What is the answer for this math problem 6x>12

k0ka [10]

Answer:

The correct answer is: " x > 2 " .

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Step-by-step explanation:

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Given the inequality:

" 6x > 12 " ;

Solve in terms of "x" :

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Divide each side of the inequality by "6" ;

to isolate "x" on one side of the inequation; & to solve in terms of "x" ;

→ " 6x / 6 > 12 / 6 " ;

to get:

→ " x > 2 " .

______________________________________________________

Hope this is helpful to you.

Best wishes to you in your academic pursuits

— and within the "Brainly" community!

______________________________________________________

4 0

3 years ago

What is 212.809 rounded to the nearest hundredth

MrRissso [65]

Answer:

212.81

Step-by-step explanation:

212.809 rounded to the nearest hundredth is 212.81

plz mark as brainliest

4 0

3 years ago

Read 2 more answers

7(x+y)^(2)+13x(x+y)-2^(2) <br> help

artcher [175]

Answer:

https://www.symbolab.com/solver/step-by-step/7%5Cleft(x%2By%5Cright)%5E%7B2%7D%2B13x%5Cleft(x%2By%5Cright)-2%5E%7B2%7D

Step-by-step explanation:

try this link

6 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