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3 years ago

Show that the equation x cubed + 8x = 30 has a solution between x = 2.2 and x =2.3 ?

1 answer:

4 0

$x^3+8x=30\\
x^3+8x-30=0\\\\
2.2^3+8\cdot2.2-30=10.648+17.6-30=-1.752\\
2.3^3+8\cdot2.3-30=12.167+18.4-30=0.567
$

For $x=2.2$ the value of $x^3+8x-30$ is negative, and for $x=2.3$ the value is positive which means between $x=2.2$ and $x=2.3$ there is an x for which the value of $x^3+8x-30$ is equal to 0 and therefore there is a solution.

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Miles brought the Russian novel Anna Kerenina. His paperback edition contains 992 page. Miles takes 3 days to read the first 50

Nesterboy [21]

Answer:

59.52 days

Step-by-step explanation:

So this is a simple problem we can solve easily

If it takes 3 days to read 50 pages then obviously his rate of reading is 50 pages per day

If we divide 992 by 50, then we can find how many 3 day increments it will take him

(992/50 is 19.84)

Now is we multiply 19.84 by 3, we get the total amount of days which is 59.52

I hope I helped and have a wonderful day!

7 0

3 years ago

4x-2=18 find what x means

MakcuM [25]

4x-2=18 -2 on both sides 4x=16 divid by 4 on both sides x= 4

6 0

4 years ago

Which of the following is the graph of y = |x - 3|

quester [9]

Answer:

<u>y = | x - 3 | is graphed on the attachment below </u>↓

Step-by-step explanation:

If you ever need an equation graphed, here's a useful site called Desmos that can do that really well and for free.

8 0

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 $\left( {a + b} \right)(a+b)$ .