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Nat2105 [25]
3 years ago
14

The average of three numbers is 45. two of the numbers are equal. the last number is 89. what are the two missing numbers?

Mathematics
2 answers:
san4es73 [151]3 years ago
5 0

Answer:23

Step-by-step explanation:

Let a, b and c be the three numbers

a + b + c / 3 = 45

a = b (given)

So 2a + c / 3 = 45

c = 89 (given)

So 2a + 89 /3 = 45

     2a + 89 = 135

     2a = 46

     <em>a= 23</em>

Since  a= b<em>, b = 23</em>

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So the numbers are 23 and 23

trasher [3.6K]3 years ago
4 0
The average of a set of data is equal to the sum of the values divided by the number of data present. So, if we have three numbers, the average would be:

let x, y and z represent the three numbers
average = x + y + z / 3 = 45

Two number are equal in value, so let x = y. Substituting the value to the expression of average,

45 = x + x + z / 3
45 = 2x + z / 3

It said that the last number is 89 so z is equal to 89.

45 = 2x + 89 / 3
135 = 2x + 89
46 = 2x
x = 23

Therefore, the two numbers are both 23.
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A TV station claims that 38% of the 6:00 - 7:00 pm viewing audience watches its evening news program. A consumer group believes
Elena L [17]

Answer:

z=\frac{0.340 -0.38}{\sqrt{\frac{0.38(1-0.38)}{830}}}=-2.374  

p_v =P(Z  

So the p value obtained was a very low value and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people that regularly watch the TV station’s news program is significantly less than 0.38 .  

Step-by-step explanation:

1) Data given and notation

n=830 represent the random sample taken

X=282 represent the people that regularly watch the TV station’s news program

\hat p=\frac{282}{830}=0.340 estimated proportion of people that regularly watch the TV station’s news program

p_o=0.38 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the proportion is less than 0.38:  

Null hypothesis:p\geq 0.38  

Alternative hypothesis:p < 0.38  

When we conduct a proportion test we need to use the z statisitc, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

3) Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.340 -0.38}{\sqrt{\frac{0.38(1-0.38)}{830}}}=-2.374  

4) Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level provided \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a left tailed test the p value would be:  

p_v =P(Z  

So the p value obtained was a very low value and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people that regularly watch the TV station’s news program is significantly less than 0.38 .  

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