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In-s [12.5K]
3 years ago
13

Which function does the graph represent? f(x) = log(x + 3) + 1 f(x) = log(x + 1) + 3 f(x) = log(x + 1) – 3 f(x) = log(x – 3) + 1

Mathematics
2 answers:
saveliy_v [14]3 years ago
8 0

Answer:

f(x) = log(x + 1) + 3

Step-by-step explanation:

plato users

Anettt [7]3 years ago
4 0
It'd be a lot easier to help you if you'd share the answer graphs.

Just so that you know:

<span>f(x) = log(x + 3) + 1 can be graphed as follows:
</span>
1.  Graph y = log x.  This function's domain is x>0.  It begins in Quadrant IV and ends in Quadrant I.  It intercepts the x-axis at (1,0).

2.  Now move the entire graph 1 unit to the left.  This gives you the graph of y = log (x+1).

3.  Now translate this entire graph up 3 units.  This gives you the graph of <span>f(x) = log(x + 3) + 1.</span>
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Answer:

Part a

We need to conduct a one tailed test

We need to conduct a hypothesis in order to check if the mean is higher than 2.5, the system of hypothesis would be:  

Null hypothesis:\mu \leq 2.5  

Alternative hypothesis:\mu > 2.5  

Part b: Calculate the statistic

We can replace in formula (1) the info given like this:  

z=\frac{3.372-2.5}{\frac{0.66}{\sqrt{5}}}=2.954    

Part c :P-value

Since is a one sided test the p value would be:  

p_v =P(z>2.954)=0.0016  

Conclusion  

If we compare the p value and the significance level assumed \alpha=0.01 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, we can conclude that the true mean is higher than 2.5 at 1% of signficance.  

Step-by-step explanation:

a. Should the alternative hypothesis be one-sided or two-sided?

b. Test the hypothesis that the mean adhesion is 2.5 dyne-cm².

c. What is the P-value of the test statistic?

Data given and notation  

Data: 2.69, 5.76, 2.67, 1.62 ,4.12

We can calculate the sample mean with this formula:

\bar X= \frac{\sum_{i=1}^n X_i}{n}

\bar X=3.372 represent the sample mean

\sigma=0.66 represent the population standard deviation

n=5 sample size  

\mu_o =2.5 represent the value that we want to test

\alpha=0.01 represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

Part a: State the null and alternative hypotheses.  

We need to conduct a one tailed test

We need to conduct a hypothesis in order to check if the mean is higher than 2.5, the system of hypothesis would be:  

Null hypothesis:\mu \leq 2.5  

Alternative hypothesis:\mu > 2.5  

If we analyze the size for the sample is < 30 but we know the population deviation so is better apply a z test to compare the actual mean to the reference value, and the statistic is given by:  

z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}  (1)  

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Part b: Calculate the statistic

We can replace in formula (1) the info given like this:  

z=\frac{3.372-2.5}{\frac{0.66}{\sqrt{5}}}=2.954    

Part c :P-value

Since is a one sided test the p value would be:  

p_v =P(z>2.954)=0.0016  

Conclusion  

If we compare the p value and the significance level assumed \alpha=0.01 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, we can conclude that the true mean is higher than 2.5 at 1% of signficance.  

8 0
3 years ago
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