During the calendar year of 1971 a total of 171 deaths were caused by influenza in a city of 450,000 persons. The temporal distribution of these deaths was as follows: First Quarter, 54; Second Quarter, 43; Third Quarter, 35; and Fourth Quarter, 39. Calculate the annual and quarterly mortality rates per 100,000 population.

Well lets see.

[tex]3(x+4)=3x+4\implies 12 = 4\implies x\notin\mathbb{C}[/tex].

There are no such x-es that satisfy the equation.

Answer:

a)  "K" is proportional Constant   K= 0.0833

b)     The value of b = 99.639

Step-by-step explanation:

Explanation :-

Given   'a' is directly proportional to 'b'

                     a ∝ b

                 a  =  k b ....(i)

where "K" is proportional Constant

Case(i):-

when a =6  and b=72

              a  =  k b    

         ⇒ 6 = k (72)

       ⇒  [tex]K = \frac{6}{72} = \frac{1}{12} = 0.0833[/tex]      

Case(ii):-      

Given  a = 8.3  

          a  =  k b    

⇒   8.3 = 0.0833 ×b

⇒  [tex]b = \frac{8.3}{0.0833} = 99.639[/tex]

Final answer:-

a)"K" is proportional Constant   K= 0.0833

b)     The value of b = 99.639

Answer: D.

Step-by-step explanation:

You want to cube each term in the parentheses. When you take an exponent to an exponent, you just multiply them. You get (27m^-12). In order to get rid of that negative exponent, you should put a one over the m term and make -12, +12:

[tex](\frac{27}{m^12} )(3m^5)[/tex]

Multiply the numerators to get:

[tex]81m^5[/tex]

You now have:

[tex]\frac{81m^5}{m^12}[/tex]

When you divide exponents, you subtract them. 5 - 12 = -7

You have m^-7 which is the same as 1/m^7. Finally, mulitply that by the 81 we left out to get the answer of D.

The expression equivalent to the given expression (3m⁻⁴)³(3m⁵) is 81/m⁷. So, option D is correct.

Exponentiation is a mathematical operation that involves two numbers, the base b, and the exponent or power n, and is pronounced as "b raised to the power of n." It is written as bⁿ and is pronounced as "b raised to the power of n."

When n is a positive integer, bⁿ = b × b × b ×...× b

and b⁻ⁿ = 1/bⁿ

If n = 0, then b⁰ = 1.

Here, (3m⁻⁴)³(3m⁵) = (3³)(m⁻⁴)³(3m⁵) = (27m⁻¹²)(3m⁵) = 81m⁵⁻¹² = 81/m⁷

Therefore, the expression equivalent to the given expression (3m⁻⁴)³(3m⁵) is 81/m⁷. So, option D is correct.

Learn more about exponentiation here -

https://brainly.com/question/14513824

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Answer:

  1.504×10⁶ ft·lb

Step-by-step explanation:

We understand the top of the oil in the tank is 12 ft below ground level, and the bottom of the tank is 8+18=26 ft below ground level. Then the average depth of the oil is (12+26)/2 = 19 ft below ground level.

The height of the oil in the tank is 26-12=14 ft, so the volume of it is ...

  V = πr²h = π(6 ft)²(14 ft) = 504π ft³ ≈ 1583.36 ft³

__

So, the work required to raise that volume of oil to the surface is ...

  (1538.36 ft³)(50 lb/ft³)(19 ft) = 1.504×10⁶ ft·lb

Answer:

They have two sets of equal answers...

Step-by-step explanation:

-2 * 2 * 4 = -16

0 - 4 * -2 * -2 = -16

0 * -2 * -2 * 4 = 0

0 * 4 * 4 = 0

Answer:

There are 6 total possibilities, 3 red faces and 3 prime numbers however, 2 and 3 are prime numbers and they are red as well so total successful outcomes = 3 + 3 - 2 = 4. This means that the answer is 4 / 6 or 2 / 3.

Answer:

[tex]\frac{2}{3}[/tex]

Step-by-step explanation:

[tex]1 \: 2\:3[/tex] are red

[tex]5[/tex] is prime.

Total of [tex]4[/tex] possibilities out of [tex]6[/tex]

[tex]\frac{4}{6}[/tex]

Answer:

a) [tex]\sigma_{\bar x} = 1.414[/tex]

b) [tex]\sigma_{\bar x} = 1.414[/tex]

c) [tex]\sigma_{\bar x} = 1.414[/tex]

d) [tex]\sigma _{\bar x} = 1.343[/tex]

Step-by-step explanation:

Given that:

The random sample is of size 50 i.e the population standard deviation  =10

Size of the sample n = 50

a) The population size is infinite;

The standard error is determined as:

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

[tex]\sigma_{\bar x} = \dfrac{10}{\sqrt{50}}[/tex]

[tex]\sigma_{\bar x} = 1.414[/tex]

b) When the population size N= 50000

n/N = 50/50000 = 0.001 < 0.05

Thus ; the finite population of the standard error is not applicable in this scenario;

Therefore;

The standard error is determined as:

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

[tex]\sigma_{\bar x} = \dfrac{10}{\sqrt{50}}[/tex]

[tex]\sigma_{\bar x} = 1.414[/tex]

c)  When the population size N= 5000

n/N = 50/5000 = 0.01 < 0.05

Thus ; the finite population of the standard error is not applicable in this scenario;

Therefore;

The standard error is determined as:

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

[tex]\sigma_{\bar x} = \dfrac{10}{\sqrt{50}}[/tex]

[tex]\sigma_{\bar x} = 1.414[/tex]

d) When the population size N= 500

n/N = 50/500 = 0.1 > 0.05

So; the finite population of the standard error is applicable in this scenario;

Therefore;

The standard error is determined as:

[tex]\sigma _{\bar x} = \sqrt{\dfrac{N-n}{N-1} }\dfrac{\sigma}{\sqrt{n} } }[/tex]

[tex]\sigma _{\bar x} = \sqrt{\dfrac{500-50}{500-1} }\dfrac{10}{\sqrt{50} } }[/tex]

[tex]\sigma _{\bar x} = 1.343[/tex]

Answer:

[tex]8x-38[/tex]

Step-by-step explanation:

[tex]3(x-6)+5(x-4)\\3x-18+5x-20\\3x+5x-18-20\\8x-38[/tex]

Answer:

21,000$

Step-by-step explanation:

part to whole method

20/100 and 4,200/

How many 20s to get to 4,200?

Answer:

The answer is A (1,-3/2)

Step-by-step explanation:

Add both x coordinates, divide by 2

Add both y coordinates, divide by 2

Answer:

meh

Step-by-step explanation:

Answer:

[tex] T_1 = 10*3.5 = 35[/tex]

[tex] T_2 = 20*2.9 = 58[/tex]

[tex] T_3 = 25*3.2 = 80[/tex]

[tex] T_4 = 15*3.4 = 51[/tex]

[tex] \bar X= \frac{T_1 +T_2 +T_3 +T_4}{10+20+25+15}= \frac{35+58+80+51}{10+20+25+15} = 3.2[/tex]

Step-by-step explanation:

For this case we have the following info given:

[tex] n_1= 10 , \bar X_1 = 3.5[/tex] for freshmen

[tex] n_2= 20 , \bar X_2 = 2.9[/tex] for sophomores

[tex] n_3= 25 , \bar X_3 = 3.2[/tex] for juniors

[tex] n_4= 15 , \bar X_4 = 3.4[/tex] for seniors

For this case we can use the formula for the sample mean in order to find the total of each group:

[tex] \bar X =\frac{\sum_{i=1}^n X_i}{n}[/tex]

[tex]T= \sum_{i=1}^n X_i = n *\bar X[/tex]

And replacing we got:

[tex] T_1 = 10*3.5 = 35[/tex]

[tex] T_2 = 20*2.9 = 58[/tex]

[tex] T_3 = 25*3.2 = 80[/tex]

[tex] T_4 = 15*3.4 = 51[/tex]

And the grand mean would be given by:

[tex] \bar X= \frac{T_1 +T_2 +T_3 +T_4}{10+20+25+15}= \frac{35+58+80+51}{10+20+25+15} = 3.2[/tex]

Answer:

The first step is to determine how many times 2x goes into 8x^3

Step-by-step explanation:

The first step is to determine how many times 2x goes into 8x^3

                     4x^2

        --------------------------

2x-1  |  (8x3 – x2 + 6x + 7

           8x^3 -4x^2

Answer:

A

Step-by-step explanation:

i just took the test

Answer:

Option A

Step-by-step explanation:

Correlation does not imply causality. Correlation shows whether and how strongly pairs of variables are related.

Causality shows a situation between two events where one event is affected by the other

We would be skeptical of this survey because it is very difficult to assume that people who owned a radio were more likely to be declared insane and put into an insane asylum as listening to the radio cannot cause insanity unless proven.

Answer:

Step-by-step explanation:

Let "a" and "b" represent the costs of one apple and one banana, respectively. Then the purchases can be written ...

  4a +b = 1.40

  7a +b = 2.00

Subtracting the first equation from the second gives ...

  (7a +b) -(4a +b) = (2.00) -(1.40)

  3a = 0.60 . . . . simplify

  a = 0.20 . . . . . .divide by 3

Using this in the first equation, we have ...

  4(0.20) +b = 1.40

  b = 0.60 . . . . . subtract 0.80

The cost of an apple is £0.20; the cost of a banana is £0.60.

Answer:

Step-by-step explanation:

Given that:

A small-business Web site contains 100 pages and 60%, 30%, and 10%  of the pages contain low, moderate, and high graphic content, respectively.

. A sample of four pages is selected without replacement,

Let  X and Y denote the number of pages with moderate and high graphics output in the sample

We are meant to determine

a)  [tex]f_{XY}(x, y)[/tex]  from the given data in the question;

However; the probability mass function can be expressed via the relation:

[tex]f_{XY}(x,y) = \dfrac{(^{30} _x ) ( ^{10} _y ) (^{60} _ {4-x-y} ) }{ ( ^{100}_4)}[/tex]

We can now have a table shown as :

[tex]X|Y[/tex]                0           1               2              3              4          Total    [tex]f_X(x)[/tex]

0              0.1244     0.0873     0.02031    0.0018     0.0001   0.234

1               0.2618     0.13542   0.02066    0.00092    0         0.419

2              0.1964     0.0666    0.00499       0              0         0.268

3              0.0621     0.01035     0                 0              0         0.073

4              0.0069       0              0                0              0          0.007

Total [tex]F_Y(y)[/tex]   0.6516   0.2996   0.0460      0.0028  0.0001    1

b) [tex]f_X(x)[/tex]

The marginal distribution definition of [tex]f_X(x)[/tex][tex]= P(X=x)[/tex]

[tex]f_X(x)[/tex] [tex]= \sum P(X=x, Y=y)[/tex]

From the table above ; the corresponding values of [tex]f_X(x)[/tex]  are :

X           0           1         2          3           4

[tex]f_X(x)[/tex]    0.234   0.419  0.268   0.073    0.007

( since [tex]f_X(x)[/tex] represent the vertical column)

c) E(X)

By using the expression [tex]E(x) = \sum ^4 _{x= 0} x f_X(x)[/tex]

we have:

E(X) = [tex]0*0.234+1*0.419+ 2*0.268+3*0.073+4*0.007[/tex]

E(X) = 0 + 0.419 + 0.536 + 0.218 + 0.028

E(X) = 1.202

d) fyß(y)

Using the thesis of conditional Probability; we have :

[tex]P(A|B) = \dfrac{ P(A,B) }{ P(B) }[/tex]

The conditional probability for the mass function is then:

[tex]f_{Y|X=3}(y) = \dfrac{f_{XY}(3,y)}{f_{X}(x)}[/tex]

where;

[tex]f_X(3) = 0.0725[/tex]

values of [tex]f_{XY} (3,y)[/tex] for every y ∈ (0,1,2,3,4)

Therefore; the mass function is:

[tex]Y|{_X_3}:\left[\begin{array}{ccccc}0&1&2&3&4\\0.857&0.143&0&0&0\\ \end{array}\right][/tex]

e) E(Y | X = 3)

By using the expression [tex]E(Y|X=3) = \sum ^4 _{y= 0} y f_{y \beta} \ (y|x)[/tex]

we have:

⇒ [tex]0 * 0.857 + 1*0.143 +0 +0+0[/tex]

= 0.143

The value of E(Y | X = 3) = 0.143

g) Are X and Y independent?

To Check if X and Y independent; Let assume if [tex]f_{XY}(x,y) = f_X(x)f_{Y}(y)[/tex] ; then we can say that X and Y are independent.

From the above previous table :

[tex]f_{(XY)} (0.4) = 0.0001[/tex]

[tex]f_X (0)[/tex] = 0.1244 + 0.087268+0.02031+ 0.001836 + 0.0001

[tex]f_X (0)[/tex]  = 0.234

[tex]f_X (4)=0.0001 +0+0 \\ \\ = 0.001[/tex]

[tex]f_{X}(0) f_Y(4) = 0.234*0.0001[/tex]

[tex]f_{X}(0) f_Y(4) = 0.00002[/tex]

We conclude that [tex]f_{(XY)} (0.4) \neq f_X(0) f_Y(y)[/tex]; As such X and Y are said to be  non - independent.

Answer:

4: 4[tex]\pi^2[/tex]

Step-by-step explanation:

2[tex]\pi[/tex] x 5 x [tex]x[/tex] = 10[tex]\pi x[/tex]

10[tex]\pi x[/tex] = 40[tex]\pi ^3}[/tex]

x = 4[tex]\pi^2[/tex]

Answer:

4π units

Step-by-step explanation:

v=lwh

40π^3=2π×5×h

40π^3=10π^2×h

h=40π^3/10π^2

h=4π units

mark brianliest if my answer suit your question please.

[tex]answer \\ 4g ^{6} + 16 \\ solution \\ ( {2g}^{3} + 4)^{2} \\ = 2 \times 2 \: g ^{3 \times 2} + 4 \times 4 \\ = 4 {g}^{6} + 16 \\ hope \: it \: helps \\ good \: luck \: on \: your \: assignment[/tex]

Answer:

4g^6+16  IS equivalent  to (2g^3+4)^2

Answer:  [tex]\bold{\dfrac{8}{17}=47.1\%}[/tex]

Step-by-step explanation:

[tex]\dfrac{\text{painter or sculptor}}{\text{total artists}}=\dfrac{6+2}{6+2+9}=\dfrac{8}{17}[/tex]

Answer:

24

Step-by-step explanation:

That would be:

(3/8)(30)

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

(15/16)(1/2)

This can be reduced in various ways.  First, divide that 30 by 15, obtaining:

   6/8

-----------

   1/32

Now invert the divisor (1/32) and multiply:

(6/8)(32/1)

This reduces to 6*4, or 24.

Answer:

The value 155 is zero standard deviations from the [population] mean, because [tex] \\ x = \mu[/tex], and therefore [tex] \\ z = 0[/tex].

Step-by-step explanation:

The key concept we need to manage here is the z-scores (or standardized values), and we can obtain a z-score using the next formula:

[tex] \\ z = \frac{x - \mu}{\sigma}[/tex] [1]

Where

Carefully looking at [1], we can interpret it as the distance from the mean of a raw value in standard deviations units. When the z-score is negative indicates that the raw score, x, is below the population mean, [tex] \\ \mu[/tex]. Conversely, a positive z-score is telling us that x is above the population mean. A z-score is also fundamental when determining probabilities using the standard normal distribution.

For example, think about a z-score = 1. In this case, the raw score is, after being standardized using [1], one standard deviation above from the population mean. A z-score = -1 is also one standard deviation from the mean but below it.

These standardized values have always the same probability in the standard normal distribution, and this is the advantage of using it for calculating probabilities for normally distributed data.

A subject earns a score of 155. How many standard deviations from the mean is the value 155?

From the question, we know that:

Having into account all the previous information, we can say that the raw score, x = 155, is zero standard deviations units from the mean. The subject   earned a score that equals the population mean. Then, using [1]:

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

[tex] \\ z = \frac{155 - 155}{50}[/tex]

[tex] \\ z = \frac{0}{50}[/tex]

[tex] \\ z = 0[/tex]

As we say before, the z-score "tells us" the distance from the population mean, and in this case this value equals zero:  

[tex] \\ x = \mu[/tex]

Therefore

[tex] \\ z = 0[/tex]

So, the value 155 is zero standard deviations from the [population] mean.

Answer:

The value of Chi-square test statistic for a hypothesis test of independence is 14.22.

Step-by-step explanation:

The data provided is for one day's output of Kortholt's from the Melodic Kortholt Company.

The formula to compute the chi-square test statistic for a hypothesis of independence is:

[tex]\chi^{2}=\sum {\frac{(O-E)^{2}}{E}}[/tex]

The formula to compute the expected frequencies (E) is:

[tex]E=\frac{\text{Row Total}\times \text{Column Total}}{N}[/tex]

Consider the Excel output attached.

Compute the value of Chi-square test statistic as follows:

[tex]\chi^{2}=\sum {\frac{(O-E)^{2}}{E}}[/tex]

    [tex]=1.333+2.222+4.000+6.667\\=14.222\\\approx 14.22[/tex]

Thus, the value of Chi-square test statistic for a hypothesis test of independence is 14.22.

Answer:

$25

Step-by-step explanation

If oliver had $43 before his birthday he was given (+) an amount of money, in order to find out  how much money was given you need to reverse the equation (-) $68-$43= $25

Answer:

Section 1:

a) 7:15 a.m - 19:15

b) 1:05 am - 01:05

c) 2:01 p.m - 14:01

d) 9:22 p.m - 21:22

e) 12:25 am- 24:25

Section 2:

a) 1155 hours - 11:55am

b) 1005 hours -10:05am

c) 1714 hours - 5:14pm

d) 0756 hours - 7:56am

e) 1345 hours- 1:45pm ​

Answer:

12:25 am= 00:25

Step-by-step explanation:

Answer:

line s and t would not meet even if you extend them and also they have the same slope and gradient

Answer:

y = -3/4x-1/4

Step-by-step explanation:

The slope intercept form of a line is

y = mx+b

where m is the slope and b is the y intercept

y = -3/4x +b

We have a point (-5,4)

4 = -3/4 (-5) +b

Changing to a common denominator

16/4 = 15/4 +b

subtracting 15/4 from each side

16/4-15/4 = -15/4 +15/4 +b

1/4 = b

y = -3/4x-1/4

Answer:

book

Step-by-step explanation:

kmgktn

Corrected Question

At the beginning of the season, Jamie pays full price($49.64) for a ticket to see the panthers, her favorite baseball team. Ticket prices decrease $0.41 for every game the panthers lose this season. the panthers currently have 33 wins and 31 losses.

(a)Represent the total change in the cost of a ticket given their losses.

(b) What is the cost of a ticket for the next game they play?

Answer:

(a)$(49.64-0.41x)

(b)$36.93

Step-by-step explanation:

(a)Cost of a Full Ticket =$49.64

Let x be the number of losses

The ticket price reduces by $0.41 for every loss

Therefore:

Ticket Price after x losses =$(49.64-0.41x)

Therefore, total change in the cost of a ticket given their losses=$(49.64-0.41x)

(b)For this season the Panthers has suffered 31 losses.

Number of Losses, x=31

Therefore, cost of a ticket for the next game they play

= $(49.64-0.41*31)

=49.64-12.71

=$36.93

Answer:

Given..hope it helps

Step-by-step explanation:

Area of square= 36cm2 = total area

Side of square= √36= 6cm

Ratio a:b = 2:1

so let's take total area as 3x

while a is 2x and b is 1x

3x= 36 (given)

x= 36/3 = 12

so area of each rectangle--

area A= 2x= 24cm2

area B= x= 12cm2

While finding the dimensions, they both have a common length since they are from the same square which will be 6cm (side)

So,

Dimensions of rectangle A= 6cm * 4cm

Dimensions of rectangle B= 6cm * 2cm

Answer:

0.4929 = 49.29% probability that he voted in favor of Scott Walker

Step-by-step explanation:

Bayes Theorem:

Two events, A and B.

[tex]P(B|A) = \frac{P(B)*P(A|B)}{P(A)}[/tex]

In which P(B|A) is the probability of B happening when A has happened and P(A|B) is the probability of A happening when B has happened.

In this question:

Event A: Having a college degree.

Event B: Voting for Scott Walker.

They found that 57% of the respondents voted in favor of Scott Walker.

This means that [tex]P(B) = 0.57[/tex]

Additionally, they estimated that of those who did vote in favor for Scott Walker, 33% had a college degree

This means that [tex]P(A|B) = 0.33[/tex]

Probability of having a college degree.

33% of those who voted for Scott Walker(57%).

45% of those who voted against Scott Walker(100 - 57 = 43%). So

[tex]P(A) = 0.33*0.57 + 0.45*0.43 = 0.3816[/tex]

What is the probability that he voted in favor of Scott Walker?

[tex]P(B|A) = \frac{0.57*0.33}{0.3816} = 0.4929[/tex]

0.4929 = 49.29% probability that he voted in favor of Scott Walker