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2 years ago

Help please ;-; The values in the table represent a linear function.

Mathematics

1 answer:

Fittoniya [83]2 years ago

4 0

Answer:

The function rule in slope-intercept form is:

$y = \frac{1}{2}x-\frac{7}{2}$

Step-by-step explanation:

The slope-intercept form of a function is given as:

$y = mx+b$

Here

m is the rate of change of function and b is the y-intercept

The rate of change is calculated as:

$m = \frac{difference\ in\ y}{difference\ in\ x}$

For this, any two pairs of input and output can be taken.

So using the pairs (1,-3) and (2,-1)

$m=\frac{2-1}{-1+3}\\=\frac{1}{2}$

Putting the value of slope in slope-intercept form

$y = \frac{1}{2}x+b$

Putting (1,-3) in the equation

$-3 = \frac{1}{2}(1)+b\\-3 = \frac{1}{2}+b\\b = -3-\frac{1}{2}\\b = \frac{-6-1}{2}\\b= \frac{-7}{2}$

Putting the value of b

$y = \frac{1}{2}x-\frac{7}{2}$

Hence,

The function rule in slope-intercept form is:

$y = \frac{1}{2}x-\frac{7}{2}$

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A development economist is studying income growth in a rural area of a developing country. The last census of the population of

kykrilka [37]

Answer:

If we compare the p value and the significance level given $\alpha=0.01$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL reject the null hypothesis, so we can say that the population mean is not singificantly higher than 425.

Step-by-step explanation:

Data given and notation

$\bar X=433.75$ represent the mean height for the sample

$\sigma=\sqrt{2500}=50$ represent the population standard deviation for the sample

$n=100$ sample size

$\mu_o =425$ represent the value that we want to test

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

z would represent the statistic (variable of interest)

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

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if the mean height actually is higher than the mean height for men in 1960, the system of hypothesis would be:

Null hypothesis: $\mu \leq 425$

Alternative hypothesis: $\mu > 425$

Since 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".

Calculate the statistic

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

$z=\frac{433.75-425}{\frac{50}{\sqrt{100}}}=1.75$