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Dennis_Churaev [7]
3 years ago
9

. In the U.S., from 2004−2015, the correlation coefficient for the relationship between the size of a cell phone data plan, x, a

nd the number of text messages sent, y, is R=+0.97. Describe the relationship between the data plan size and the number of text messages sent in the U.S.
Mathematics
1 answer:
bonufazy [111]3 years ago
4 0

Answer: strong positive correlafion between data plan size 'x' and number of text messages sent 'y'

Step-by-step explanation:

'R' in statistics is used to denote correlation Coefficient. The correlation Coefficient is a value which ranges between -1 to +1. It tells us the level of relationship or correlation which exists between the relative movement of two variables, in this case the relationship between data plan size and the number of text messages sent in the US. R value of 0 depicts that no relationship exists between the two variables, R value closer the R value is to +1 and - 1 depicts the strength of positive and negative correlation of the two variables respectively.

A R value of +0.97 in the context above, depicts a strong positive correlation between data plan size and number of text messages sent in the US. That is large data size usually corresponds to large number of text messages and vice versa.

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In a random sample of males, it was found that 28 write with their left hands and 210 do not. In a random sample of females, it
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Answer:

a) Null hypothesis:p_{M} \geq p_{W}  

Alternative hypothesis:p_{M} < p_{W}  

b) z=\frac{0.118-0.125}{\sqrt{0.122(1-0.122)(\frac{1}{238}+\frac{1}{497})}}=-0.271    

c)p_v =P(Z   

d) If we compare the p value and the significance level given \alpha=0.05 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the the proportion of men that write with their left hand is NOT significant lower than the proportion of female that write with their left hand

Step-by-step explanation:

1) Data given and notation  

X_{M}=28 represent the number of men that write with their left hand

X_{W}=62 represent the number of women  that write with their left hand

n_{M}=210+28=238 sample of male selected

n_{W}=62+435=497 sample of female selected

p_{M}=\frac{28}{238}=0.118 represent the proportion of men  that write with their left hand

p_{W}=\frac{62}{497}=0.125 represent the proportion of women that write with their left hand

\alpha=0.05 represent the significance level

z would represent the statistic (variable of interest)  

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

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the rate of left-handedness among males is less than that among females , the system of hypothesis would be:  

Null hypothesis:p_{M} \geq p_{W}  

Alternative hypothesis:p_{M} < p_{W}  

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

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

Where \hat p=\frac{X_{M}+X_{W}}{n_{M}+n_{W}}=\frac{28+62}{238+497}=0.122

3) Calculate the statistic

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

z=\frac{0.118-0.125}{\sqrt{0.122(1-0.122)(\frac{1}{238}+\frac{1}{497})}}=-0.271  

4) Statistical decision

We have a significance level provided \alpha=0.05, and now we can calculate the p value for this test.  

Since is a one left side test the p value would be:  

p_v =P(Z  

If we compare the p value and the significance level given \alpha=0.05, 0,1,0.15 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the the proportion of men that write with their left hand is NOT significant loer than the proportion of female that write with their left hand .  

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