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Alex787 [66]
2 years ago
13

If the log↓b(a)=0, what is the value of a?explain why log↓0 (3) and log↓1 (3) do not exist. ​

Mathematics
1 answer:
Sloan [31]2 years ago
5 0

Answer:

1. a = 1

2. See explanation below.

Step-by-step explanation:

<u>First Question</u>

Given:

\displaystyle \large{\log_b a = 0}

Convert to exponential:

\displaystyle \large{\log_b a = c \to b^c = a}

Thus \displaystyle \large{\log_b a = 0 \to b^0 = a}

Evaluate:

\displaystyle \large{b^0 = a}

We know that for every values to power of 0 will always result in 1, excluding 0 to power of 0 itself.

Solution:

\displaystyle \large{a = 1}

__________________________________________________________

<u>Second Question</u>

Given:

\displaystyle \large{log_0 3} and \displaystyle \large{\log_1 3}

Let’s convert to an equation:

\displaystyle \large{\log_0 3 = x} and \displaystyle \large{\log_1 3 = y}

The variables represent unknown values of logarithm.

Convert to exponential:

\displaystyle \large{0^x = 3} and \displaystyle \large{1^y = 3}

Notice that none of x-values and y-values will satisfy the equations. No matter what real numbers you put in, these equations will always be false.

Hence, no solutions for x and y.

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prohojiy [21]

Answer:

z=\frac{0.253 -0.24}{\sqrt{\frac{0.24(1-0.24)}{75}}}=0.264  

p_v =2*P(z>0.264)=0.792  

So the p value obtained was a very high value and using the significance level given \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of students said that blue is their favorite color is not different from 0.24

Step-by-step explanation:

Data given and notation

n=75 represent the random sample taken

X=19 represent the students said that blue is their favorite color

\hat p=\frac{19}{75}=0.253 estimated proportion of  students said that blue is their favorite color

p_o=0.24 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)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion is different from 0.24.:  

Null hypothesis:p=0.24  

Alternative hypothesis:p \neq 0.24  

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.

Calculate the statistic  

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

z=\frac{0.253 -0.24}{\sqrt{\frac{0.24(1-0.24)}{75}}}=0.264  

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 bilateral test the p value would be:  

p_v =2*P(z>0.264)=0.792  

So the p value obtained was a very high value and using the significance level given \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of students said that blue is their favorite color is not different from 0.24

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