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3 years ago

14

Which equation is closest to the line of best fit in the graph below?

1 answer:

Tomtit [17]3 years ago

3 0

Answer:

b will the correct answer plzz lock b and win 1 lakh

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1. Evaluate each expression without using a calculator.<br> (a) <img src="https://tex.z-dn.net/?f=%28-3%29%5E%7B4%7D" id="TexFor

Rufina [12.5K]

The result of the exponential expression is 81

<h3>Indices expressions</h3>

Indices are written in term of exponents

According to the expoenent law of indices

a^4 = a * a * a * a

Given the expression

(-3)^4

This means the product of -3 in four places. Mathematically

(-3)^4 = -3 * -3 * -3 * -3
(-3)^4 = 9 * 9
(-3)^4 = 81

Hence the result of the exponential expression is 81

Learn more on exponents here: brainly.com/question/11975096

5 0

2 years ago

I NEED HELP ASAP PLEASE!

dusya [7]

Answer:

The length of AC = 4 and the length of A'C' = 1 so the scale factor is 1/4.

8 0

3 years ago

2.2 Your friend Sam, mistakenly wrote down the multiples of 10 as: 1; 2; 5; and 10.

kkurt [141]

Do you know the multiples of 10

6 0

2 years ago

Daniel ran 5 kilometers in 40 minutes. Andy ran 4,550 meters in 37 minutes. Who ran faster?

gtnhenbr [62]

Answer:

Daniel

Step-by-step explanation:

Daniel ran 5000/40=500=4=125 meters in 1 minutes

Andy ran 4550/37=122.9729... some less than 123 meters in second

Daniel was faster than Andy

4 0

3 years ago

Standard Error from a Formula and a Bootstrap Distribution Sample A has a count of 30 successes with and Sample B has a count of

tia_tia [17]

Answer:

Using a formula, the standard error is: 0.052

Using bootstrap, the standard error is: 0.050

Comparison:

The calculated standard error using the formula is greater than the standard error using bootstrap

Step-by-step explanation:

Given

Sample A Sample B

$x_A = 30$ $x_B = 50$

$n_A = 100$ $n_B =250$

Solving (a): Standard error using formula

First, calculate the proportion of A

$p_A = \frac{x_A}{n_A}$

$p_A = \frac{30}{100}$

$p_A = 0.30$

The proportion of B

$p_B = \frac{x_B}{n_B}$

$p_B = \frac{50}{250}$

$p_B = 0.20$

The standard error is:

$SE_{p_A-p_B} = \sqrt{\frac{p_A * (1 - p_A)}{n_A} + \frac{p_A * (1 - p_B)}{n_B}}$

$SE_{p_A-p_B} = \sqrt{\frac{0.30 * (1 - 0.30)}{100} + \frac{0.20* (1 - 0.20)}{250}}$

$SE_{p_A-p_B} = \sqrt{\frac{0.30 * 0.70}{100} + \frac{0.20* 0.80}{250}}$

$SE_{p_A-p_B} = \sqrt{\frac{0.21}{100} + \frac{0.16}{250}}$

$SE_{p_A-p_B} = \sqrt{0.0021+ 0.00064}$

$SE_{p_A-p_B} = \sqrt{0.00274}$

$SE_{p_A-p_B} = 0.052$

Solving (a): Standard error using bootstrapping.

Following the below steps.

Open Statkey
Under Randomization Hypothesis Tests, select Test for Difference in Proportions
Click on Edit data, enter the appropriate data
Click on ok to generate samples
Click on Generate 1000 samples ---- <em>see attachment for the generated data</em>

From the randomization sample, we have:

Sample A Sample B

$x_A = 23$ $x_B = 57$

$n_A = 100$ $n_B =250$

$p_A = 0.230$ $p_A = 0.228$

So, we have:

$SE_{p_A-p_B} = \sqrt{\frac{p_A * (1 - p_A)}{n_A} + \frac{p_A * (1 - p_B)}{n_B}}$

$SE_{p_A-p_B} = \sqrt{\frac{0.23 * (1 - 0.23)}{100} + \frac{0.228* (1 - 0.228)}{250}}$

$SE_{p_A-p_B} = \sqrt{\frac{0.1771}{100} + \frac{0.176016}{250}}$

$SE_{p_A-p_B} = \sqrt{0.001771 + 0.000704064}$

$SE_{p_A-p_B} = \sqrt{0.002475064}$

$SE_{p_A-p_B} = 0.050$

5 0

3 years ago