All categories

2 years ago

9x two the second power = 1

2 answers:

6 0

Answer:Set the factor '(-1 + x + 4x2)' equal to zero and attempt to solve: Simplifying -1 ... Divide all terms by 4 the coefficient of the squared term: Divide each side by '4'.

bbbbbbSet the factor '(-1 + x + 4x2)' equal to zero and attempt to solve: Simplifying -1 ... Divide all terms by 4 the coefficient of the squared term: Divide each side by '4'.

Set the factor '(-1 + x + 4x2)' equal to zero and attempt to solve: Simplifying -1 ... Divide all terms by 4 the coefficient of the squared term: Divide each side by '4'.

Step-by-step explanation:

Zepler [3.9K]2 years ago

5 0

Rewrite

(

)

(

)

−

Rewrite

(

)

−

Since both terms are perfect squares, factor using the difference of squares formula,

−

(

)

(

−

)

where

and

(

)

(

−

)

You might be interested in

Solve the following problem. 3/8×3/4=

mel-nik [20]

Answer: 9/32

Step-by-step explanation: Multiply Straight across.

Brainliest please

3 0

2 years ago

Need help fast plz for my pre calc exam

bezimeni [28]

Answer:

h = 8.54 units

Step-by-step explanation:

The Law of Cosines

It relates the length of the sides of a triangle with one of its internal angles.

Let a,b, and c be the length of the sides of a given triangle, and x the included angle between sides a and b, then the following relation applies:

$c^2=a^2+b^2-2ab\cos x$

Since we know the values of all three side lengths, we solve the equation for x:

$\displaystyle \cos x=\frac{a^2+b^2-c^2}{2ab}$

For the triangle ABC in the image, a=10, b=15, c=13, thus:

$\displaystyle \cos A=\frac{10^2+15^2-13^2}{2*10*15}$

$\displaystyle \cos A=\frac{156}{300}$

$\displaystyle \cos A=0.52$

Thus, A = 58.67°

For the right triangle of height h and hypotenuse 10, we use the sine ratio:

$\displaystyle \sin 58.67^\circ=\frac{h}{10}$

Solving for h:

$h = 10\sin 58.67^\circ$

h = 8.54 units

6 0

3 years ago

How can I solve this? and can you please tell me how step by step.

Ludmilka [50]

Answer:27/343 or 0.0787172

Step-by-step explanation:

First you need to place the exponent on both the numerator and the demonimator to make 3 to the power of 3 over 7 to the power of 3

Next you evaluate the numerator so 3 to the power of 3 is 27

and 7 to the power of 3 is 343 so your answer in fraction form is 27/343

you can also change into a decimal if you divide the fraction if you need to

Hope this helps

8 0

2 years ago

Read 2 more answers

A researcher used a sample of n = 60 individuals to determine whether there are any preferences among six brands of pizza. Each

Blizzard [7]

Answer:

1) χ² ≥ 11.07

2) Goodness of fit test, df: χ² $_{3}$

Independence test, df: χ² $_{1}$

The goodness of fit test has more degrees of freedom than the independence test.

3) $e_{females.} = 80$

4) H₀: $P_{ij}= P_{i.} * P_{.j}$ ∀ i= 1, 2, ..., r and j= 1, 2, ..., c

5) χ² $_{6}$

Step-by-step explanation:

Hello!

The researcher took a sample of n=60 people and made them taste proof samples of six different brands of pizza and choose their favorite brand, their choose was recorded. So the study variable is the following:

X: favorite pizza brand, categorized in brand 1, brand 2, brand 3, brand 4, brand 5 and brand 6.

The Chi-square goodness of fit test is done with the following statistic:

χ²= ∑ $\frac{(O_i-E_i)^2}{E_i}$ ≈χ² $_{k-1}$

Where k represents the number of categories of the study variable. In this example k= 6.

Remember, the rejection region for the Chi-square tests of "goodnedd of fit", "independence", and "homogeneity" is allways one-tailed to the right. So you will only have one critical value.

χ² $_{k-1; 1 - \alpha }$

χ² $_{6-1; 1 - 0.05 }$

χ² $_{5; 0.95 }$ = 11.070

This means thar the rejection region is χ² ≥ 11.07

If the Chi-Square statistic is equal or greather than 11.07, then you reject the null hypothesis.

The statistic for the goodness of fit is:

χ²= ∑ $\frac{(O_i-E_i)^2}{E_i}$ ≈χ² $_{k-1}$

Degrees of freedom: χ² $_{k-1}$

In the example: k= 4 (the variable has 4 categories)

χ² $_{4-1}$ = χ² $_{3}$

The statistic for the independence test is:

χ²= ∑∑ $\frac{(O_ij-E_ij)^2}{E_ij}$ ≈χ² $_{(r-1)(c-1)}$ ∀ i= 1, 2, ..., r & j= 1, 2, ..., c

If the information is in a contingency table

r= represents the total of rows

c= represents the total of columns

In the example: c= 2 and r= 2

Degrees of freedom: χ² $_{(r-1)(c-1)}$

χ² $_{(2-1)(2-1)}$ = χ² $_{1}$

The goodness of fit test has more degrees of freedom than the independence test.

To calculate the expected frecuencies for the independence test you have to use the following formula.

$e_{ij} = n * P_i. * P_.j = n * \frac{o_i.}{n} * \frac{o_.j}{n}$

Where o_i. represents the total observations of the i-row, o_.j represents the total of observations of the j-column and n is the sample size.

Now, this is for the expected frequencies in the body of the contingency table, this means the observed and expected frequencies for each crossing of categories is not the same.

On the other hand, you would have the totals of each category and population in the margins of the table (subtotals), this is the same when looking at the observed frequencies and the expected frequencies. Wich means that the expected frequency for the total of a population is the same as the observed frequency of said population. A quick method to check if your calculations of the expected frequencies for one category/population are correct is to add them, if the sum results in the subtotal of that category/population, it means that you have calculated the expected frequencies correctly.

The expected frequency for the total of females is 80

Using the formula:

(If the females are in a row) $e_{females.} = 100 * \frac{80}{100} * \frac{0}{100}$

$e_{females.} = 80$

There are two ways of writing down a null hypothesis for the independence test:

Way 1: using colloquial language

H₀: The variables X and Y are independent

Way 2: Symbolically

H₀: $P_{ij}= P_{i.} * P_{.j}$ ∀ i= 1, 2, ..., r and j= 1, 2, ..., c

This type of hypothesis follows from the definition of independent events, where if we have events A and B independent of each other, the probability of A and B is equal to the product of the probability of A and the probability of B, symbolically: P(A∩B) = P(A) * P(B)

In this example, you have an independence test for two variables.

Variable 1, has 3 categories

Variable 2, has 4 categories

To follow the notation, let's say that variable 1 is in the rows and variable 2 is in the columns of the contingency table.

The statistic for this test is:

χ²= ∑∑ $\frac{(O_ij-E_ij)^2}{E_ij}$ ≈χ² $_{(r-1)(c-1)}$ ∀ i= 1, 2, ..., r & j= 1, 2, ..., c

In the example: c= 3 and r= 4

Degrees of freedom: χ² $_{(r-1)(c-1)}$

χ² $_{(3-1)(4-1)}$ = χ² $_{6}$

I hope you have a SUPER day!

4 0

3 years ago

Write each fraction as a sum or difference 14-6x/19

Oksanka [162]

Given number : 14 - 6x / 19
So we need to write this fraction as a sum or difference.
First, simplify the given number:
=> 14 – 6x / 19
=> 14 x 19 – (6x)
 19
=> 266 – 6x
 19
=> 266 – 6x = -2 * (3x - 133)
Thus, the final result would be:
=> -2 * (3x - 133) => This will be the fraction sum or difference of the given number
 19

8 0

2 years ago