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2 years ago

12

Find the value of x.

1 answer:

Gemiola [76]2 years ago

3 0

Answer:

15

Step-by-step explanation:

Hope this helps!

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What y=Mx+b <br>A, a slope formula<br>B, math<br>C, y-intercept

FinnZ [79.3K]

Answer:

Slope-intercept form

Step-by-step explanation:

The correct answer is actually slope-intercept form.

6 0

3 years ago

Read 2 more answers

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

2 years ago

A relationship between two variables is described below. We can think of one variable as helping to explain the other. Is the in

kramer

Answer:

Explanatory Variable

Step-by-step explanation:

The variable that we can change is called the Explanatory variable.

The response variable dependent upon the explanatory variable, as we change the value of the explanatory variable the value of the response variable is also gets changed.

The number of years smoking a cigarette is in our control so it is an explanatory variable.

and, the impact of the number of years smoking a cigarette is directly on lung capacity, so it is Response variable.

3 0

3 years ago

Please help with 16 and 17 those are hard

notka56 [123]

The answer to number 17 is c

6 0

3 years ago

They are 13 sales people at a car dealership last year they each sold the same number of cars together they sold 1157 how many c

bonufazy [111]

Answer: each salesperson sold 89 cars last year.

Step-by-step explanation:

The total number of sales people at the dealership shop is 13.

Last year they each sold the same number of cars. The total number of cars that they sold together last year was 1157. Therefore, the number of cars that each salesperson sold would be

Total number of cars sold/ number of salespersons

It becomes

1157/13 = 89

3 0

2 years ago