Please answer this correctly without making mistakes

It's easy it's called Two-way tables please help

Vesnalui [34]

Answer: The filled out table is shown below in the attached image

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Explanation:

The letters A through J are one way to fill out the table. Though there are other possible orders.

Start at letter A, which is from the fact we have 40 people total

Then move to letter B. This is the total number who like pasta (26)

We have C = A-B = 40-26 = 14 people who don't like pasta

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Now move to cell D. This is the total who don't like netball, which is 21 people. There are E = A-D = 40-21 = 19 people who do like netball.

F = 4 is the number of people who don't like either thing (netball or pasta). So G = D-F = 21-4 = 17 people like pasta but don't like netball.

Of those people who like netball (E = 19), we have 9 who also like pasta. This is in cell H in the upper left corner. This means J = E-H = 19-9 = 10 people like netball but don't like pasta.

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So we have these values

A = 40
B = 26
C = 14
D = 21
E = 19
F = 4
G = 17
H = 9
J = 10

7 0

3 years ago

<img src="https://tex.z-dn.net/?f=%20%5Csqrt%7B1%7D%20" id="TexFormula1" title=" \sqrt{1} " alt=" \sqrt{1} " align="absmiddle" c

AveGali [126]

Is 1 because 1 times 1 equals the desired 1

4 0

4 years ago

Read 2 more answers

Please help me quickly asap ksososososozxo

svlad2 [7]

Answer: I can barley see -_-

Step-by-step explanation:

7 0

2 years ago

Liam is setting up folding chairs for a meeting. If he arranges the chairs in 6 rows of the same length, he has 11 chairs left o

uranmaximum [27]

Answer:

25

Step-by-step explanation:

8 0

3 years ago

Read 2 more answers

In a study of 420,095 Danish cell phone users, 135 subjects developed cancer of the brain or nervous system (based on data from

Maksim231197 [3]

Answer:

$z=\frac{0.0003214 -0.00034}{\sqrt{\frac{0.00034(1-0.00034)}{420095}}}=-0.654$

$p_v =2*P(Z$

So the p value obtained was a very high value and using the significance level given $\alpha=0.005$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say that the true proportion not differs significantly from the specified value of 0.00034 or 0.034%.

Step-by-step explanation:

1) Data given and notation

n=420095 represent the random sample taken

X=135 represent the subjects developed cancer of the brain or nervous system (based on data from the Journal of the National Cancer Institute as reported in USA Today)

$\hat p=\frac{135}{420095}=0.0003214$ estimated proportion of subjects developed cancer of the brain or nervous system (based on data from the Journal of the National Cancer Institute as reported in USA Today)

$p_o=0.00034$ is the value that we want to test

$\alpha=0.005$ represent the significance level

Confidence=99.5% or 0.995

z would represent the statistic (variable of interest)

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

2) Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the brain or nervous system at a rate that is different from the rate of 0.0340% :

Null hypothesis: $p=0.00034$

Alternative hypothesis: $p \neq 0.00034$

When we conduct a proportion test we need to use the z statistic, 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 $p_o$ .

3) Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.0003214 -0.00034}{\sqrt{\frac{0.00034(1-0.00034)}{420095}}}=-0.654$

4) 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 $\alpha=0.005$ . The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(Z$

So the p value obtained was a very high value and using the significance level given $\alpha=0.005$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say that the true proportion not differs significantly from the specified value of 0.00034 or 0.034%.

4 0

3 years ago