Which formula used in probability to find Independence question

Answer:

16.24

Step-by-step explanation:

of means multiply

28% * 58

Change to decimal form

.28 * 58

16.24

Answer:

[tex]\Large \boxed{\mathrm{16.24}}[/tex]

Step-by-step explanation:

[tex]28\% \times 58[/tex]

[tex]\displaystyle \sf Apply \ percentage \ rule : a\%=\frac{a}{100}[/tex]

[tex]\displaystyle \frac{28}{100} \times 58[/tex]

[tex]\sf Multiply.[/tex]

[tex]\displaystyle \frac{1624}{100} =16.24[/tex]

Answer:

x ≤ [tex]\frac{9}{5}[/tex]

Step-by-step explanation:

Given

[tex]\frac{1}{4}[/tex](12x + 8) ≤ - 2x + 11 ← distribute parenthesis on left side

3x + 2 ≤ - 2x + 11 ( add 2x to both sides )

5x + 2 ≤ 11 ( subtract 2 from both sides )

5x ≤ 9 ( divide both sides by 5 )

x ≤ [tex]\frac{9}{5}[/tex]

-¼(12x+8) ≤ -2x+11

4X-¼(12x+8) ≤-2x+11

= -12x + 8 ≤ -2x + 11

-12x + 2x ≤ 11 - 8

= -10x/10 ≤ 3/-10

Answer:

The two choices are true by CPCTC. Are there other choices that were not posted?

Answer:

4 cups of flour is needed and 4/3 cups of sugar

Step-by-step explanation:

Given

2 dozen Muffins; 3 cups of flour and 1 cup of sugar

Required

Determine the cups of flour if 18 muffins is used

First, we have to determine the proportion of the number of muffins used previously and now;

Represent this with p;

[tex]p = \frac{2\ dozen}{18}[/tex]

[tex]p = \frac{2 * 12}{18}[/tex]

[tex]p = \frac{24}{18}[/tex]

[tex]p = \frac{4}{3}[/tex]

Multiply this to the previous cups of flours and sugars;

Cups of flour = p * previous cups of flour

[tex]Cups\ of\ flour = \frac{4}{3} * 3[/tex]

[tex]Cups\ of\ flour = 4[/tex]

Cups of Sugar = p * previous cups of sugar

[tex]Cups\ of\ sugar= \frac{4}{3} * 1[/tex]

[tex]Cups\ of\ sugar= \frac{4}{3}[/tex]

Hence, 4 cups of flour is needed and 4/3 cups of sugar

Answer:

  18

Step-by-step explanation:

Each exterior angle is the supplement of the adjacent interior angle, so is ...

  180° -160° = 20°

The total of all n of these exterior angles is 360°, so we have ...

  n(20°) = 360°

  n = 18 . . . . . . . . . divide by 20°

The polygon is an 18-gon. It has 18 sides.

Answer:

18 Sides

Step-by-step explanation:

Each interior angle = 160°

Each exterior angle = 180° - 160° = 20°

The sum of the exterior angles = 360°

Hence the number of exterior angles =360°/20°

= 18

The polygon has 18 sides (since it has 18 exterior angles).

Hope this helps.

Please mark me as Brainliest.

Answer:

1/3

Step-by-step explanation:

there are twelve marbles total. there are 4 blue marbles.

4/12 = 1/3

let the function be [tex]y=ax^2+bx+c[/tex]

put $x=0, \, y=6$ , to get $c=6$

put $x=2, \, y=16$ , $16=4a+2b+6\implies 2a+b=5$

put $x=3, \, y=33$ , $33=9a+3b+6\implies 3a+b=9$

subtract the two equation, to get $a=4$

now substitute $a$ in first equation, to get $b=5-2\cdot4=-3$

so, $f(x)=4x^2-3x+6$

Answer:63

Step-by-step explanation:

Answer:

B. ​No, because the probability of success is different for each trial.

The experiment is not binomial.

Step-by-step explanation:

The trials are not independent  because they are chosen without replacement.

There are successes and failures but the trials are dependent.

So it is not binomial.

When the balls are not replaced the probability of success becomes different for each ball.

Suppose  we have 10 balls and we pick out 1 so the p1 = 1/10

but when we again pick out another without replacement the p2= 1/9

This explains why it is not binomial. In binomial the n is fixed.

Answer:

Angle E.

Step-by-step explanation:

Hope this helps!

Answer:

a) P [ X < 24 mm ] = 0,3015          or     P [ X < 24 mm ] =  30,15 %

b) P [ X > 32 mm ]  = 0,1251          or        P [ X > 32 mm ]  = 12,51 %

c) P [  25 < X < 30 ] = 0,4964      or     P [  25 < X < 30 ] = 49,64 %

d) z(s) = 0,84

Step-by-step explanation:

Normal Distribution    N (  μ₀  ;   σ )   is  N ( 26,5 ; 4,8 )

a) P [ X < 24 mm ] = ( X - μ₀ ) / σ

P [ X < 24 mm ] = (24 - 26,5)/ 4,8 = - 0,5208 ≈ - 0,52

P [ X < 24 mm ] = - 0,52  

And from z-table we find area for z score

P [ X < 24 mm ] = 0,3015          or     P [ X < 24 mm ] =  30,15 %

b)P [ X > 32 mm ]  =  1  - P [ X < 32 mm ]

P [ X < 32 mm ]  = ( 32 - 26,5 ) / 4,8

P [ X < 32 mm ]  = 5,5/4,8  =  1,1458 ≈ 1,15

P [ X < 32 mm ]  = 1,15

And from z-table  we get

P [ X < 32 mm ]  = 0,8749

Then:

P [ X > 32 mm ]  =  1  -  0,8749

P [ X > 32 mm ]  = 0,1251          or        P [ X > 32 mm ]  = 12,51 %

c) P [  25 < X < 30 ] = P [ X < 30 ] - P [ X < 25 ]

P [ X < 30 ]  = 30 - 26,5 / 4,8   =  0,73

From  z-table    P [ X < 30 ]  =  0,7673

P [ X < 25 ] = 25 - 26,5 / 4,8  = - 0,3125  ≈  - 0,31

From z-table  P [ X < 25 ] =  0,2709

Then

P [  25 < X < 30 ] =  0,7673 -  0,2709

P [  25 < X < 30 ] = 0,4964      or     P [  25 < X < 30 ] = 49,64 %

d) If  20 %

z- score for 20% is from z-table

z(s) = 0,84

Answer:

The correct answer is:

The samples are independent because there is not a natural pairing between the two samples. (d.)

Step-by-step explanation:

Paired samples or dependent samples are samples in which natural matching or coupling occur, thus creating a data set where data from one sample is uniquely paired to another sample because they are from related groups. Examples are: pre-test/post-test data gotten before and after an intervention, samples from siblings, twins, couples etc.

On the other hand, independent or unpaired samples are those data sets that are gotten from unrelated groups, these type of samples are gotten by matching randomly sampling two unrelated groups without first matching the subjects. In our example, the sample from randomly selected women and men are not paired and unrelated, hence they are independent samples.

The samples are independent because there is not a natural pairing between the two samples. Hence, option (D) is correct.

Let us understand both the events in a systematic manner to answer this question.

Independent Events:

The simple way to understand the events, If the events are not related to each other, then the events are independent of each other. If one event is dependent on another then it is not an independent event.

Example:

Event 1: Toss a coin.

Event 2: Roll a die.

Both the events are independent of each other.

Dependent Events:

The simple way to understand the events, If the events are related to each other, then the events are independent of each other. If one event is dependent on another then it is not an independent event.

Example:

Event 1: Toss a coin.

Event 2: If head appears then roll a die.

Both the events are dependent on each other.

Thus, the samples are independent because there is not a natural pairing between the two samples.

To know more about it, please refer to the link:

https://brainly.com/question/12138721

[tex]10[/tex] divisions between $15.59$ and $15.6$ so each division is $\frac{15.60-15.59}{10}=0.001$

A is 5 division from $15.59$, so, A is $15.59+5\times 0.001=15.595$

similarly, C is 4 division behind $15.59$ so it is $15.590-4\times0.001=15.586$

and B is $15.601$

Answer:

542

Step-by-step explanation:

We are required to find the sample size at 98% confidence interval in this question

E = 0.04

P* = 20% = 0.20

n = p* x (1-p)(Zα/2÷E)²

α = 1 - 0.98

= 0.02

To get Critical value

= 0.02/2 = 0.01

The critical value at 0.01 is 2.33

Inserting values into formula:

O.2 x 0.8(2.33/0.04)²

= 0.8 x 0.2 x 58.25²

= 542.89

The value of n must be an integer therefore the answer is 542.

Answer:

72 58 62 38 44 66 42 49 76 52 ( arrange it!)

38 42 44 49 52 58 62 66 72 76 (done!)

Median: Find the number in the middle after we arranged, so the answer is (52+58)/2= 110/2 = 55

Mode : None (there is no number appear more than other number)

Mean = (38+42+44+49+52+58+62+66+72+76)/10

=559/100

=5,5

Hope it helps ^°^

Answer:

Since the critical f-value of the test statistic is less than the f value of 2.9130, we will fail to reject the null hypothesis and conclude that there's no sufficient evidence to support the claim that there is a difference in the variation in the listening times for men and women

Step-by-step explanation:

We are given;

Sample size for men; n1 = 13

Sample size for women; n2 = 11

standard deviation for men; s1 = 8 minutes

Standard deviation for women; s2 = 18 minutes.

Significance level; α = 0.1

Let's state the hypothesis;

Null hypothesis;H0: (μ1)² = (μ2)²

Alternative hypothesis;Ha: (μ1)² ≠ (μ2)²

The value of the test statistic would be;

F = (s1)²/(s2)²

F = 8²/18² = 0.1975

Now, degree of freedom for n1 is;

DF1 = n1 - 1

DF1 = 13 - 1

DF1 = 12

Also, degree of freedom for n2 is;

DF2 = 11 - 1

DF2 = 10

Now, since it's two tailed, we will make use of α/2 for the F-distribution table.

Thus, α/2 = 0.1/2 = 0.05

So,from the f-table attached, at df1 = 12 and df2 = 10,the F-Critical value is;

F_α/2 = 2.9130

Since,the critical f-value of the test statistic is less than 2.9130, we will fail to reject the null hypothesis and conclude that there's no sufficient evidence to support the claim that there is a difference in the variation in the listening times for men and women

Answer:

The answer is below

Step-by-step explanation:

The Freeman family barbecued veggie burgers, corn cobs, and mushroom caps. 3/8 of the items barbecued are veggie burgers, and 1/3 of the items barbecued are corn cobs.

Let the total number of berbecued items be x. Therefore:

x = barbecued veggie burgers + barbecued corn cobs + barbecued mushroom caps

Barbecued veggie burgers = (3/8)x, barbecued corn cobs = (1/3)x, Let barbecued mushroom caps be y

Substituting:

x = (3/8)x + (1/3)x + y

Multiply through by 24

24x = 9x + 8x + 24y

24x = 17x + 24y

24y = 24x - 17x

24y = 7x

y = (7/24)x

barbecued mushroom caps = (7/24) of items

7/24 of the items barbecued are mushroom caps

Using fractions, it is found that the fraction of barbecued items that are mushroom caps is of [tex]\frac{7}{24}[/tex].

---------------------------

---------------------------

Thus:

[tex]\frac{3}{8} + \frac{1}{3} + x = 1[/tex]

Then:

[tex]\frac{3\times3 + 8\times1 + 24x}{24} = 1[/tex]

[tex]\frac{17 + 24x}{24} = 1[/tex]

[tex]17 + 24x = 24[/tex]

[tex]24x = 7[/tex]

[tex]x = \frac{7}{24}[/tex]

The fraction of barbecued items that are mushroom caps is of [tex]\frac{7}{24}[/tex].

A similar problem is given at https://brainly.com/question/4231000

Answer:

ans right down there

Step-by-step explanation:

Here,Part 1

if the circle has a radius r so,

15 = r theta

here, theta is in radian.

Part 2

[tex]theta = \frac{15}{6} = 2.5[/tex]

part 3

[tex]theta = \frac{2.5 \times 180}{\pi} [/tex]

or theta =

143.2394487827058021919953870352629258310136811664108038729006

Answer:

Step-by-step explanation:

We first examine a simple hidden Markov model (HMM). We observe a sequence of rolls of a four-sided die at an "occasionally dishonest casino", where at time t the observed outcome x_t Element {1, 2, 3, 4}. At each of these times, the casino can be in one of two states z_t Element {1, 2}. When z_t = 1 the casino uses a fair die, while when z_t = 2 the die is biased so that rolling a 1 is more likely. In particular: p (x_t = 1 | z_t = 1) = p (x_t = 2 | z_t = 1) = p (x_t = 3 | z_t = 2) = p (x_t = 4 | z_t = 1) = 0.25, p (X_t = 1 | z_t = 2) = 0.7, p (X_t = 2 | z_t = 2) = p (X_t = 3 | z_t = 2) = p (X_t = 4 | z_t = 2) = 0.1. Assume that the casino has an equal probability of starting in either state at time t = 1, so that p (z1 = 1) = p (z1 = 2) = 0.5. The casino usually uses the same die for multiple iterations, but occasionally switches states according to the following probabilities: p (z_t + 1 = 1 | z_t = 1) = 0.8, p (z_t = 2) = 0.9. The other transition probabilities you will need are the complements of these. a. Under the HMM generative model, what is p (z1 = z2 = z3), the probability that the same die is used for the first three rolls? b. Suppose that we observe the first two rolls. What is p (z1 = 1 | x1 = 2, x2 = 4), the probability that the casino used the fair die in the first roll? c. Using the backward algorithm, compute the probability that we observe the sequence x1 = 2, x2 = 3, x3 = 3, x4 = 3 and x5 = 1. Show your work (i.e., show each of your belief for based on time). Consider the final distribution at time t = 6 for both p (z_t = 1) = p (z_t = 2) = 1.

ANSWER:

Let say we have that the first state of the die is state 1. Therefore the probability of this is p(z1=1)=0.5.

Also the probability that the same die is used(i.e. casino would be in the same state) is p(z2=1|z1=1)=0.8.

Again, suppose the first state of the die is state 2. So, p(z1=2)=0.5 and p(z2=2|z1=2)=0.9.

Other transition probabilities can be written as

p(zt+1=2|zt=1)=1-p(zt+1=1|zt=1)=.2

p(zt+1=1|zt=2)=1-p(zt+1=2|zt=2)=.1

p(z3=1|z1=1) = [p(z3=1|z2=2)*p(z2=2|z1=1)]+[p(z3=1|z2=1)*p(z2=1|z1=1)] = 0.1*0.2+0.8*0.8 = 0.66

p(z3=2|z1=2) = [p(z3=2|z2=2)*p(z2=2|z1=2)]+[p(z3=2|z2=1)*p(z2=1|z1=2)] = 0.9*0.9+0.2*0.1 = 0.83

With this, the total probability that the same die is used for the first three rolls (i.e. casino would be in the same state) is  given thus;

{p(z1=1)*p(z3=1|z1=1)}*{p(z1=2)*p(z3=2|z1=2)}

=  0.5*0.66+0.5*0.83 = 0.745

Prob = 0.745

Answer:

Given the information in the question;

a) The parameter of interest is the population of artists who are left-handed and its is 10% = (10/1000 = 0.10

b) The Null hypothesis and alternative hypothesis are;

H₀ : p = 0.10

H₁ : p > 0.10

c) The sample proportion is calculated as:

p = number of left handed artist / sample size

p = 26 / 200

p = 0.13

d) To find the p-value, The researcher should calculate the probability that the sample proportion would be 0.13 or larger for a sample of size 200 if the population proportion is actually 0.10.

Complete question is;

A machine used to fill gallon-sized paint cans is regulated so that the amount of paint dispensed has a mean of 128 ounces and a standard deviation of 0.20 ounce. You randomly select 35 cans and carefully measure the contents. The sample mean of the cans is 127.9 ounces. Does the machine need to be? reset? Explain your reasoning.

(yes/no)?, it is (very unlikely/ likely) that you would have randomly sampled 35 cans with a mean equal to 127.9 ?ounces, because it (lies/ does not lie) within the range of a usual? event, namely within (1 standard deviation, 2 standard deviations 3 standard deviations) of the mean of the sample means.

Answer:

Yes, we should reset the machine because it is unusual to have a mean equal to 127.9 from a random sample of 35 as the mean of 127.9 doesn't fall within range of a usual event with 2 standard deviations of the mean of the sample means.

Step-by-step explanation:

We are given;

Mean: μ = 128

Standard deviation; σ = 0.2

n = 35

Now, formula for standard error of mean is given as;

se = σ/√n

se = 0.2/√35

se = 0.0338

Normally, the range of values should be within 2 standard deviations of mean. In this case, normal range of values will be;

μ ± 2se = 128 ± 0.0338

This gives; 127.9662, 128.0338

So, Yes, we should reset the machine because it is unusual to have a mean equal to 127.9 from a random sample of 35 as the mean of 127.9 doesn't fall within range of a usual event with 2 standard deviations of the mean of the sample means.

Answer:

2.

Step-by-step explanation:

The first numbers in the ordered pairs are the x values;

Difference = 1 - 3 = -1

The absolute value is 2.

An absolute value of |x| {modulus of x} is the value of a real number x. The absolute value of the difference in the x-values between (1,7) and (3,11)​ is 2.

An absolute value of |x| {modulus of x} is the value of a real number x, the value we get is always a non-negative number, for example, |-5| will give 5, and also, |5| will give 5 as well.

Given the two coordinates (1, 7) and (3, 11)​ this can be written as,

(x₁ , y₁) = (1, 7)

(x₂ , y₂) = (3, 11)

Now, the absolute value of the difference in the x-values between (1,7) and (3,11)​ can be written as,

Absolute difference = |x₁ - x₂|

                                 = |1 - 3|

                                 = |-2|

                                 = 2

Hence, the absolute value of the difference in the x-values between (1,7) and (3,11)​ is 2.

Learn more about Absolute value here:

https://brainly.com/question/1301718

#SPJ2

Answer:

b. steepest slope

Step-by-step explanation:

The cumulative relative frequency curve also known as Ogive is used for reading the median, upper quartile, lower quartile from the curve and calculating the semi-interquartile range when needed.

From the cumulative relative frequency curve, the interval with the highest proportion of measurements is the interval with the steepest slope. This is because the cumulative relative frequency curve always have a positive slope, and given that the interval has the highest proportion, then the slope will be steepest.

[tex]\displaystyle\\(a+b)^n\\T_{r+1}=\binom{n}{r}a^{n-r}b^r\\\\\\(x+2)^7\\a=2x\\b=3\\r+1=4\Rightarrow r=3\\n=5\\T_4=\binom{5}{3}\cdot (2x)^{5-3}\cdot3^3\\T_4=\dfrac{5!}{3!2!}\cdot 4x^2\cdot27\\T_4=\dfrac{4\cdot5}{2}\cdot 4x^2\cdot27\\\\T_4=1080x^2[/tex]

Answer: 600 students.

Step-by-step explanation:

Ok, we start with 15,000 students.

40% of them had tuition, so the actual number of them that had tuition is:

15,000*0.40 = 6,000.

Now we want to find the number of students that studied math and science.

50% only studied math,

30% only studied science

10% studied other subjects.

So 50% + 30% + 10% did NOT studied both math and science

90% is the percentage that did not study math and mathematics as well as science, then the other 10% did.

Then, out of the 6,000 students that had tuition, 10% studied math and science, the total number is:

6,000*0.10 = 600

Answer:

88%.

Step-by-step explanation:

Multiply the fraction by 100:

(22/25) * 100

= 22 * 4

= 88%.

Answer:

The probability is  [tex]P( \= X \ge 70 ) = 0.07311[/tex]

Step-by-step explanation:

From the question we are told that

    The  population mean is  [tex]\mu = 68[/tex]

      The standard deviation is  [tex]\sigma = \sqrt{36} = 6[/tex]

      The  sample size is  [tex]n = 19[/tex]

Generally the standard error of the mean is mathematically represented as  

            [tex]\sigma_{\= x } = \frac{\sigma }{\sqrt{n} }[/tex]

=>         [tex]\sigma_{\= x } = \frac{6 }{\sqrt{19} }[/tex]

=>         [tex]\sigma_{\= x } = 1.3765[/tex]

Generally the probability that their average score will be at least 70 is mathematically represented as

            [tex]P( \= X \ge 70 ) = 1 - P( \= X < 70 ) = 1 - P(\frac{ \= X - \mu }{\sigma_{\= x}} < \frac{70 - 68}{ 1.3765} )[/tex]

Generally [tex]\frac{ \= X - \mu }{\sigma_{\= x}} = z(The \ z-score \ of \ \= X )[/tex]

So

          [tex]P( \= X \ge 70 ) = 1 - P( \= X < 70 ) = 1 - P(Z <1.453 )[/tex]

From the z-table

            [tex]P(Z <1.453 ) = 0.92689[/tex]

=>          [tex]P( \= X \ge 70 ) = 1 - P( \= X < 70 ) = 1 - 0.92689[/tex]

=>         [tex]P( \= X \ge 70 ) = 1 - P( \= X < 70 ) = 0.07311[/tex]

=>          [tex]P( \= X \ge 70 ) = 0.07311[/tex]

Answer: P(X<6) = 0.3085 or 30.85%

Step-by-step explanation: Determine, first, z-score:

[tex]z = \frac{x-\mu}{\sigma}[/tex]

x is a random variable for time a student takes to find a spot, in this case, x=6:

[tex]z = \frac{6-6.5}{1}[/tex]

z = -0.5

Using z-score table, find z-score:

P(X<6) = P(z< -0.5)

P(X<6) = 0.3085

Probability of finding a parking spot in less than 6 minutes is approximately 30.85%.

Answer:

3,069

Step-by-step explanation:

The sequence is doubling, so terms 1 through 10 are:

3, 6, 12, 24, 48, 96, 192, 384, 768, 1,536

3 + 6 + 12 + 24 + 48 + 96 + 192 + 384 + 768 + 1,536 = 3,069

Answer:

The answer is "[tex]\bold{\frac{2}{5}\ \ and \ \ \frac{6}{13}}[/tex]".

Step-by-step explanation:

You have 4/10 opportunities to choose a white ball, and there'll be 7 white balls and 6 black balls out of 13, and so the second time they choose a white one is 7/13, as well as the second time they choose a black, 6/13. people will also have a 4/10 chance.  

There are 6/10 chances which users pick its black ball and 4 white balls would still be picked, but 9 black balls and out 13 balls and thus, its second and third time you select the white one is 4/13 but you are likely to pick a black for the second time is 9/13.  

Taking the diagram of the next tree. The very first draw is marked with a and the second draw is marked with b.

[tex]\to P(a) = \frac{4}{10}\ \ \ \ \ \ \ \ \ P(b) = \frac{6}{10}\\\\\to P(\frac{a2}{a1}) = \frac{7}{13} \ \ \ \ \ \ \ \ \ \ P(\frac{a}{b}) = \frac{4}{13}\\\\\to P(\frac{b2}{a1}) = \frac{6}{13} \ \ \ \ \ \ \ \ \ \ P(\frac{b2}{b1}) = \frac{9}{13}[/tex]

Calculating the second drawn ball is white:

[tex]\to P(b2)=P(a)P(\frac{a2}{b1})+P(b)P(\frac{a}{b})\\[/tex]

              [tex]=\frac{4}{10}\frac{7}{13}+\frac{6}{10}\frac{4}{13}\\\\=\frac{28}{130}+\frac{24}{130}\\\\=\frac{28+24}{130}\\\\=\frac{52}{130}\\\\=\frac{2}{5}\\\\[/tex]

In point b:

[tex]\to P(\frac{b}{a1})= \frac{P(B)P(\frac{a}{b})}{P(a)P(\frac{a2}{b1})+P(b)P(\frac{a}{b})\\}[/tex]

              [tex]=\frac{\frac{6}{10} \frac{4}{13}}{\frac{52}{130}}\\\\=\frac{\frac{24}{130}}{\frac{52}{130}}\\\\=\frac{24}{130} \times \frac{130}{52}\\\\=\frac{24}{52}\\\\=\frac{6}{13}\\[/tex]