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3 years ago

Hi i need help asap TvT

Mathematics

2 answers:

marissa [1.9K]3 years ago

7 0

Answer:

answer is 1

Step-by-step explanation:

the x coordinate, -1.5, is negative so you must go to the left 1.5 on the x axis. then y is also negative at, -1, so you must go from the -1.5 on the x axis down one to -1

Sergio [31]3 years ago

4 0

Answer:

1 is the answer

Step-by-step explanation:

bc the first number represent x and the second y

(x,y)

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scZoUnD [109]

There are 2 instances of hhh (all girls) in the 50 trials, so the experimental probability is 2/50 = 4/100 = 0.04.

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4 years ago

-10x + 35 + 5x = -5x + 20 PLs fix this error and answer it can you also show me the steps so I understand?

Vedmedyk [2.9K]

Answer:

-10x + 35 + 5x simplifies to -5x + 35.

Step-by-step explanation:

Combine Like Terms:

= −10x + 35 + 5x

= (−10x + 5x) + (35)

= −5x + 35

Hope this helps!

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2 years ago

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dexar [7]

Answer:i would say 1

Step-by-step explanation:

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3 years ago

Read 2 more answers

Applying GCF and LCM to fraction Operations?<br>.<br>. PLZ HELP

I am Lyosha [343]

When multiplying fractions just multiply the numerator and denominators together, then simplify the fraction you get.

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You should get 20/8. Now you have to add 20/8 and 3/8. The only thing you add is the numerator, so you should get 23/8 as a final answer.

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3 years ago

A data mining routine has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so) an

Firlakuza [10]

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, $0.9664 \times 100 = 96.64$

6 0

3 years ago