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2 years ago

This graph displays a linear function. Interpret the constant rate of change of the relationship.

Mathematics

2 answers:

IgorC [24]2 years ago

4 0

Answer: -3/-1 or 3/1 is the rate of change

Step-by-step explanation:

(0,2)

(3,3) 0-3==-3

2-3= -1

-3/-1

weeeeeb [17]2 years ago

3 0

Answer:

The rate of change ( or slope) is 3.

Step-by-step explanation:

The formula for slope is y2-x2 over y1-x1. Easier terms: subtract two points from eachother, y being the numerator and x being denominator. Two points on this graph are (2,0) and (3,3). When you put y on top, you get 0/2-3/3. The answer is -3/-1, which is equal to 3

A much easier way when you're graph looks like this, is to count the units up/down and right/left, putting the up/down number on top. Since it goes 3 up and 1 right, you get 3/1, or 3.

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QUESTION THREE (30 MARKS) 3.1 The mass of a standard loaf of white bread is, by law meant to be 700g with a population standard

kiruha [24]

Using the normal distribution and the central limit theorem, it is found that there is a 0.0284 = 2.84% probability of finding a sample mean mass of 695g or below.

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Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

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Mean of 700g means that $\mu = 700$
Standard deviation of 21g means that $\sigma = 21$
Sample of 64, thus $n = 64$
<u>For the sampling distribution of the sample mean</u>, the standard deviation is of $s = \frac{21}{\sqrt{64}} = \frac{21}{8} = 2.625$

The probability of finding a sample mean mass of 695g or below is the p-value of Z when X = 695, thus:

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{695 - 700}{2.625}$

$Z = -1.905$

$Z = -1.905$ has a p-value of 0.0284.

0.0284 = 2.84% probability of finding a sample mean mass of 695g or below.

A similar problem is given at brainly.com/question/22934264

7 0

2 years ago

Find the area of quadrilateral ABCD. [Hint: the diagonal divides the quadrilateral into two triangles.]

Vadim26 [7]

Answer:

B) 28.53 unit²

Step-by-step explanation:

The diagonal AD divides the quadrilateral in two triangles:

Triangle ABD
Triangle ACD

Area of Quadrilateral will be equal to the sum of Areas of both triangles.

i.e.

Area of ABCD = Area of ABD + Area of ACD

Area of Triangle ABD:

Area of a triangle is given as:

$Area = \frac{1}{2} \times base \times height$

Base = AB = 2.89

Height = AD = 8.6

Using these values, we get:

$Area = \frac{1}{2} \times 2.89 \times 8.6 = 12.43$

Thus, Area of Triangle ABD is 12.43 square units

Area of Triangle ACD:

Base = AC = 4.3

Height = CD = 7.58

Using the values in formula of area, we get:

$Area = \frac{1}{2} \times 4.3 \times 7.58 = 16.30$

Thus, Area of Triangle ACD is 16.30 square units

Area of Quadrilateral ABCD:

The Area of the quadrilateral will be = 12.43 + 16.30 = 28.73 units²

None of the option gives the exact answer, however, option B gives the closest most answer. So I'll go with option B) 28.53 unit²

7 0

2 years ago

NEED HELP ASAP !!!!!!!

AURORKA [14]

♫ - - - - - - - - - - - - - - - ~Hello There!~ - - - - - - - - - - - - - - - ♫

➷Yes.

Explain: This is because if you feel normal, you might have a little bit of willpower to do something, which will effect the statistical outcome. if you are confident, you will have a higher statistical outcome. (Example: A sport game. Feeling: Normal, Confident, Random) If you feel random, you could get a really bad score or a really high score, but you don't know because it is random.

✽

➶ Hope This Helps You!

➶ Good Luck (:

➶ Have A Great Day ^-^

DOGE

6 0

2 years ago

r Flag For Review A certain city with a population of 132,000 is to be divided into 11 voting districts, and no district is to h

Alex787 [66]

Answer:

$P = \frac{132000}{12}=11000$

So then P =11000 is the minimum that the least populated district could have.

Step-by-step explanation:

We have a big total of N = 132000 for the population.

And we know that we divide this population into 11 districts

And we have this info given "no district is to have a population that is more than 10 percent greater than the population of any other district"

Let's assume that P represent our minimum value for a district in the population. The range of possible values for the population of each district would be between P and 1.1 P

The interest on this case is find the minimum value for P and in order to do this we can assume that 1 district present the minimum and the other 10 the maximum value 1.1P in order to find which value of P satisfy this condition, and we have this:

$P + 10 (1.1P) = 12 P= 132000$

$P = \frac{132000}{12}=11000$

So then P =11000 is the minimum that the least populated district could have.

3 0

2 years ago

7 girls audition for 12 roles in a school play. What is the probability that at least 2 of the girls audition for the same part?

Sophie [7]

Answer:

Step-by-step explanation:

This is one minus the probability that all the girls audition for different roles. The total number of ways of assigning roles to the girls is 12^7, because to each of the 7 girls, you have a choice of 12 roles.

Then if each girl is to receive a different role, then there are 12!/5! possibilities for that. If you start assigning roles to the girls, then for the first girl, there are 12 choices, but for the next you have to choose one of the 11 different ones, so 11 for the next, and then one of the 10 remaining for the next etc. etc., and this is 12*11*10*...*6 = 12!/(12-7)! =12!/5!

The probability that a random assignment of one of the 12^7 roles would happen to be one of the 12!/5! roles where each girl has a different role, is

(12!/5!)/12^7 = 12!/(12^7 5!)

Then the probability that two or more girls addition for the same part is the probability that not all the girls are assigned different roles, this is thus:

1 - 12!/(12^7 5!)

6 0

2 years ago