Ask question

Ask question

All categories

3 years ago

14

A study states that 34% of people prefer their eggs crambled. you randomly select 7 people who had egs for breakfast. what is th

e standard deviation for this distributions

1 answer:

Darya [45]3 years ago

4 0

Answer:

Mean of the binomial distribution μ = 2.38

Standard deviation of the binomial distribution σ = 1.2533

Step-by-step explanation:

<u><em>Explanation</em></u>:-

Given Population proportion

p = 34 % = 0.34

q = 1- p

= 1 -0.34

= 0.66

q = 0.66

Mean of the binomial distribution

μ = n p = 2.38

Standard deviation of the binomial distribution

σ = √n p q = 1.2533

You might be interested in

Modeling Radioactive Decay In Exercise, complete the table for each radioactive isotope.

Travka [436]

Answer :

The amount after 1000 years will be, 5.19 grams.

The amount after 10000 years will be, 0.105 grams.

Step-by-step explanation :

Half-life = 1599 years

First we have to calculate the rate constant, we use the formula :

$k=\frac{0.693}{t_{1/2}}$

$k=\frac{0.693}{1599\text{ years}}$

$k=4.33\times 10^{-4}\text{ years}^{-1}$

Now we have to calculate the amount after 1000 years.

Expression for rate law for first order kinetics is given by:

$t=\frac{2.303}{k}\log\frac{a}{a-x}$

where,

k = rate constant = $4.33\times 10^{-4}\text{ years}^{-1}$

t = time passed by the sample = 1000 years

a = initial amount of the reactant = 8 g

a - x = amount left after decay process = ?

Now put all the given values in above equation, we get

$1000=\frac{2.303}{4.33\times 10^{-4}}\log\frac{8}{a-x}$

$a-x=5.19g$

Thus, the amount after 1000 years will be, 5.19 grams.

Now we have to calculate the amount after 10000 years.

Expression for rate law for first order kinetics is given by:

$t=\frac{2.303}{k}\log\frac{a}{a-x}$

where,

k = rate constant = $4.33\times 10^{-4}\text{ years}^{-1}$

t = time passed by the sample = 10000 years

a = initial amount of the reactant = 8 g

a - x = amount left after decay process = ?

Now put all the given values in above equation, we get

$10000=\frac{2.303}{4.33\times 10^{-4}}\log\frac{8}{a-x}$

$a-x=0.105g$

Thus, the amount after 10000 years will be, 0.105 grams.

4 0

4 years ago

Simplify. 4*3 · 4*4

viktelen [127]

A)4*16

because 4*3•4*4•4*9
you have to add the exponents

3+4+9=16
keep the number

so 4*16 is the answer

4 0

3 years ago

I NEED HELPP PLZ Which equation best represents the relationship shown in this graph?

Dafna11 [192]

Answer:

y = 2x

the formula for linear equations are y = mx+c,

where m is the gradient,

and c is the y-intercept

to find m (the gradient):

1. pick to points on the graph (eg. -2,-4 and 2,4)

2 substitute the values into the formula for gradient y2-y1/x2-x1.

m = y2-y1/x1-x2

= -4 -4/-2-2

= -8/-4

= 2

to find c (y-intercept):

- the y-intercept is where the graph cuts the y axis

- in this graph, the y-intercept is 0

hence,

c = 0

substitute m = 2 and c = 0 to y = mx+c,

y = 2x + 0

y = 2x

hence, the equation that best represents the relationship shown in the graph is y = 2x.

8 0

2 years ago

A genetic experiment involving peas yielded one sample of offspring consisting of 420 green peas and 174 yellow peas. Use a 0.01

slavikrds [6]

Answer:

a) $z=\frac{0.293 -0.23}{\sqrt{\frac{0.23(1-0.23)}{594}}}=3.649$

b) For this case we need to find a critical value that accumulates $\alpha/2$ of the area on each tail, we know that $\alpha=0.01$ , so then $\alpha/2 =0.005$ , using the normal standard table or excel we see that:

$z_{crit}= \pm 2.58$

Since the calculated value is higher than the critical value we have enough evidence to reject the null hypothesis at 1% of significance.

Step-by-step explanation:

Data given and notation

n=420+174=594 represent the random sample taken

X=174 represent the number of yellow peas

$\hat p=\frac{174}{594}=0.293$ estimated proportion of yellow peas

$p_o=0.23$ is the value that we want to test

$\alpha=0.01$ represent the significance level

Confidence=99% or 0.99

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 of yellow peas is 0.23:

Null hypothesis: $p=0.23$

Alternative hypothesis: $p \neq 0.23$

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:

$z=\frac{0.293 -0.23}{\sqrt{\frac{0.23(1-0.23)}{594}}}=3.649$

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:

$p_v =2*P(z>3.649)=0.00026$

So the p value obtained was a very low value and using the significance level given $\alpha=0.05$ we have $p_v$ so we can conclude that we have enough evidence to reject the null hypothesis.

b) Critical value

For this case we need to find a critical value that accumulates $\alpha/2$ of the area on each tail, we know that $\alpha=0.01$ , so then $\alpha/2 =0.005$ , using the normal standard table or excel we see that:

$z_{crit}= \pm 2.58$

Since the calculated value is higher than the critical value we have enough evidence to reject the null hypothesis at 1% of significance.

5 0

3 years ago

Helpppppppppppppppppppp

PIT_PIT [208]

Answer:

$( {4}^{3} \div {5}^{ - 2} {)}^{5}$

Step-by-step explanation:

${4}^{15} . {5}^{10}$

<em>hope</em><em> </em><em>this</em><em> </em><em>will</em><em> </em><em>help</em><em> </em><em>you</em><em> </em><em>more</em><em> </em>

<em>have</em><em> </em><em>a</em><em> </em><em>great</em><em> </em><em>day</em><em>.</em><em>.</em>

5 0

3 years ago

Read 2 more answers