Can u help me answer dis

PLZ HELP ASAP!!!! if image doesn't come thru wait for me to edit it

Vitek1552 [10]

One of the factors of one hundred is 20

7 0

4 years ago

Please help me in this question

charle [14.2K]

Number defective=4
number of non-defective=total-defective
=20-4
=16
the questions asked for 1 defective
so we choose only 1 defective from 4 defective items
4C1

and for 1 non-defective
we choose only 1 non-defective from 16 non-defective items
16C1

we choose 2 items from 20 items
so 20C2

answer:
probability= [(4C1) * (16C1)] /(20C2)
=32/95

6 0

3 years ago

2) The results of a 2012 Pew Foundation survey of high school and middle school teachers is given in the pie chart. A student as

Serggg [28]

Answer:

The calculated value z = 9.4451 > 1.96 at 5% level of significance.

Null hypothesis is rejected at 5% level of significance

yes there is difference in the distribution of types of cell phones for the teachers in 2018 at a 5% level of significance

Step-by-step explanation:

Explanation:-

Step:- (1)

The results of a 2012 Pew Foundation survey of high school and middle school teachers is given in the pie chart.

A student asked a random sample of teachers in 2018 and found 165 had smart-phones, 80 had a cell phone

The first sample proportion

$p_{1} = \frac{80}{165} = 0.4848$

A student asked a random sample of teachers in 2018 and found 165 had smart-phones,5 had no cell phone

The second sample proportion

$p_{2} = \frac{5}{165} = 0.03030$

Step :-(ii)

Null hypothesis :H₀: Assume that there is no difference in the distribution of types of cell phones for the teachers in 2018

H₀ : p₁ = p₂

Alternative hypothesis :H₁

H₁ : p₁ ≠ p₂

Level of significance : ∝=0.05

The tabulated value z=1.96

Step:-(iii)

The test statistic

$Z = \frac{p_{1} -p_{2} }{\sqrt{pq(\frac{1}{n_{1} } } +\frac{1}{n_{2} } )} }$

where $p = \frac{n_{1}p_{1} +n_{2} p_{2} }{n_{1} + n_{2} }$

q = 1-p

In given data n₁ = n₂ = n

$p = \frac{165 (0.4848)+165 (0.03030 }{165 + 165}$

on calculation , we get p = 0.2655

q =1-p = 1-0.2655

q = 0.7345

$Z = \frac{0.4848 -0.030}{\sqrt{0.2655X0.7345(\frac{1}{165 } } +\frac{1}{165} )} }$

Z = 9.4451

The calculated value z = 9.4451 > 1.96 at 5% level of significance.

Conclusion:-

Null hypothesis is rejected at 5% level of significance

yes there is difference in the distribution of types of cell phones for the teachers in 2018 at a 5% level of significance

6 0

4 years ago

Timothy deposited $2,780.20 in a savings account that earns 4.3% simple interest. What will Timothy’s account balance be in 7 mo

julia-pushkina [17]

Keeping in mind that, there are 12 months in a year, therefore, 7 months is really just 7/12 of a year.

$\bf \qquad \textit{Simple Interest Earned Amount}\\\\
A=P(1+rt)\qquad 
\begin{cases}
A=\textit{accumulated amount}\\
P=\textit{original amount deposited}\to& \$2780.20\\
r=rate\to 4.3\%\to \frac{4.3}{100}\to &0.043\\
t=years\to &\frac{7}{12}
\end{cases}
\\\\\\
A=2780.20\left(1+0.043\cdot \frac{7}{12} \right)$

7 0

3 years ago

Read 2 more answers

Your teacher will report the mean and standard deviation of the sampling distribution created by the class.

sukhopar [10]

Answer:

$\hat p = \frac{\sum_{i=1}^{40} \hat p_i}{40}$

$\hat p = 0.493$

And the deviation is given by this formula:

$s_{\hat p}= \frac{\sum_{i=1}^{40} (\hat p_i - \hat p)^2}{n-1}= 0.085$

And as we can see the population proportion expected for the number of heads 0.5 is very close to the mean of the sampling distribution, the error is :

$\% Error = \frac{0.5-0.493}{0.5}* 100 = 1.4\%$

Step-by-step explanation:

Assuming the data on the figure attached. We ar assuming that this is a sampling distribution of sample proportions of heads in 40 flips of a coin.

As we can see we have the following values:

0.25, 0.35, 0.375,0.375, 0.40,0.40,0.40, 0.425,0.425,0.425, 0.45,0.45,0.45,0.45, 0.475,0.475,0.475, 0.475,0.475, 0.50,0.50,0.50, 0.525,0.525,0.525,0.525, 0.55,0.55,0.55,0.55,0.55, 0.575,0.575,0.575 0.575, 0.575, 0.60,0.60, 0.65,0.65

And we can calculate the sample proportion with the following formula:

$\hat p = \frac{\sum_{i=1}^{40} \hat p_i}{40}$

$\hat p = 0.493$

And the deviation is given by this formula:

$s_{\hat p}= \frac{\sum_{i=1}^{40} (\hat p_i - \hat p)^2}{n-1}= 0.085$

And as we can see the population proportion expected for the number of heads 0.5 is very close to the mean of the sampling distribution, the error is :

$\% Error = \frac{0.5-0.493}{0.5}* 100 = 1.4\%$

4 0

3 years ago