Simplify 100y^3/98xy pls answer soon hegarty maths lazy

In the book Essentials of Marketing Research, William R. Dillon, Thomas J. Madden, and Neil H. Firtle discuss a research proposa

MakcuM [25]

Answer:

Null hypothesis: $p_{1} = p_{2}$

Alternative hypothesis: $p_{1} \neq p_{2}$

$z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500$

$p_v =2*P(Z>0.500)=0.617$

So the p value is a very low value and using any significance level for example $\alpha=0.05, 0,1,0.15$ always $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.

Step-by-step explanation:

Data given and notation

$X_{1}=25$ represent the number of homeowners who would buy the security system

$X_{2}=9$ represent the number of renters who would buy the security system

$n_{1}=140$ sample 1

$n_{2}=60$ sample 2

$p_{1}=\frac{25}{140}=0.179$ represent the proportion of homeowners who would buy the security system

$p_{2}=\frac{9}{60}= 0.15$ represent the proportion of renters who would buy the security system

z would represent the statistic (variable of interest)

$p_v$ represent the value for the test (variable of interest)

Concepts and formulas to use

We need to conduct a hypothesis in order to check if the two proportions differs , the system of hypothesis would be:

Null hypothesis: $p_{1} = p_{2}$

Alternative hypothesis: $p_{1} \neq p_{2}$

We need to apply a z test to compare proportions, and the statistic is given by:

$z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}$ (1)

Where $\hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{25+9}{140+60}=0.17$

Calculate the statistic

Replacing in formula (1) the values obtained we got this:

$z=\frac{0.179-0.15}{\sqrt{0.17(1-0.17)(\frac{1}{140}+\frac{1}{60})}}=0.500$

Statistical decision

For this case we don't have a significance level provided $\alpha$ , but we can calculate the p value for this test.

Since is a two sided test the p value would be:

$p_v =2*P(Z>0.500)=0.617$

So the p value is a very low value and using any significance level for example $\alpha=0.05, 0,1,0.15$ always $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions NOT differs significantly.

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2 years ago

What is 4973 divided by 7

Firlakuza [10]

The answer is 710.42

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2 years ago

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The resultant of a certain system of forces has the X and Y components shown in Fig. 220. Determine the components of this resul

Alchen [17]

First, you need to determine the resultant force and its angle. This one is real easy, since you only have one (x) and one (y) component. X = 300 and Y = 480

1) sqrt (300^2 + 480^2) = ? (round your answer) 
2) tanθ = y/x Solving for θ: θ = tan^-1(y/x): θ = ? (round your answer) 

Now, you should have a resultant force value and its angle, from zero, in the first quadrant and between the Y and N axes. Draw yourself a diagram showing all of the axes, the resultant and the angles. You're going to have to do some very easy math to determine the angles between the Y and N axes and the resultant. Call these new angles α and β. α is the angle between N and the resultant and β is the angle between T and the resultant. Hint: one of them is 28 deg. 

Once you've gotten those figured, the Y and N axes become your new axis, ignore the X and Y. Find the X and Y components of the resultant (again). ? * cos(α) = 500 and ? * sin(β) = 266 (round your answers)

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1 year ago

A portfolio manager summarizes the input from the macro and micro forecasters in the following table

jasenka [17]

The awnser to this question is Macro Forecasts

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2 years ago

Write two expressions where the solution is 41

Marina CMI [18]

40+1=41
10×4+1=41
that is what I have so there you go

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2 years ago