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hjlf
3 years ago
7

While her husband spent 2½ hours picking out new speakers, a statistician decided to determine whether the percent of men who en

joy shopping for electronic equipment is higher than the percent of women who enjoy shopping for electronic equipment. The population was Saturday afternoon shoppers. Out of 66 men, 23 said they enjoyed the activity. Eight of the 23 women surveyed claimed to enjoy the activity. Interpret the results of the survey. Conduct a hypothesis test at the 5% level. Let the subscript m = men and w = women.
State the distribution to use for the test. (Round your answers to four decimal places.)
Mathematics
1 answer:
AVprozaik [17]3 years ago
4 0

Answer:

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

z=\frac{0.34848-0.34782}{\sqrt{0.34831(1-0.34831)(\frac{1}{66}+\frac{1}{23})}}=0.0057  

p_v =P(Z>0.0057)=0.4977  

The p value is a very high value and using the significance level \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 percent of men who enjoy shopping for electronic equipment is NOT significantly higher than the percent of women who enjoy shopping for electronic equipment.  

Step-by-step explanation:

1) Data given and notation  

X_{M}=23 represent the number of men that said they enjoyed the activity of Saturday afternoon shopping

X_{W}=8 represent the number of women that said they enjoyed the activity of Saturday afternoon shopping

n_{M}=66 sample of male selected

n_{W}=23 sample of demale selected

p_{M}=\frac{23}{66}=0.34848 represent the proportion of men that said they enjoyed the activity of Saturday afternoon shopping

p_{W}=\frac{8}{23}=0.34782 represent the proportion of women with red/green color blindness  

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 percent of men who enjoy shopping for electronic equipment is higher than the percent of women who enjoy shopping for electronic equipment , the system of hypothesis would be:  

Null hypothesis:p_{M} \leq 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{23+8}{66+23}=0.34831

3) Calculate the statistic

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

z=\frac{0.34848-0.34782}{\sqrt{0.34831(1-0.34831)(\frac{1}{66}+\frac{1}{23})}}=0.0057  

4) Statistical decision

Using the significance level provided \alpha=0.05, the next step would be calculate the p value for this test.  

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

p_v =P(Z>0.0057)=0.4977  

So the p value is a very high value and using the significance level \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 percent of men who enjoy shopping for electronic equipment is NOT significantly higher than the percent of women who enjoy shopping for electronic equipment.  

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  • a. See the table below
  • b. See the table below
  • c. 0.548
  • d. 0.576
  • e. 0.534
  • f) i) 0.201, ii) 0.208

Explanation:

First, order the information provided:

Table: "Who is better at getting deals?"

                                       Who Is Better?

Respondent      I Am        My Spouse     We Are Equal

Husband           278             127                     102

Wife                   290            111                       102

<u>a. Develop a joint probability table and use it to answer the following questions. </u>

The<em> joint probability table</em> shows the same information but as proportions. Hence, you must divide each number of the table by the total number of people in the set of responses.

1. Number of responses: 278 + 127 + 102 + 290 + 111 + 102 = 1,010.

2. Calculate each proportion:

  • 278/1,010 = 0.275
  • 127/1,010 = 0.126
  • 102/1,010 = 0.101
  • 290/1,010 = 0.287
  • 111/1,010 = 0.110
  • 102/1,010 = 0.101

3. Construct the table with those numbers:

<em>Joint probability table</em>:

Respondent      I Am        My Spouse     We Are Equal

Husband           0.275           0.126                 0.101

Wife                   0.287           0.110                  0.101

Look what that table means: it tells that the joint probability of being a husband and responding "I am" is 0.275. And so for every cell: every cell shows the joint probability of a particular gender with a particular response.

Hence, that is why that is the joint probability table.

<u>b. Construct the marginal probabilities for Who Is Better (I Am, My Spouse, We Are Equal). Comment.</u>

The marginal probabilities are calculated for each for each row and each column of the table. They are shown at the margins, that is why they are called marginal probabilities.

For the colum "I am" it is: 0.275 + 0.287 = 0.562

Do the same for the other two colums.

For the row "Husband" it is 0.275 + 0.126 + 0.101 = 0.502. Do the same for the row "Wife".

Table<em> Marginal probabilities</em>:

Respondent      I Am        My Spouse     We Are Equal     Total

Husband           0.275           0.126                 0.101             0.502

Wife                   0.287           0.110                  0.101             0.498

Total                 0.562           0.236                0.202             1.000

Note that when you add the marginal probabilities of the each total, either for the colums or for the rows, you get 1. Which is always true for the marginal probabilities.

<u>c. Given that the respondent is a husband, what is the probability that he feels he is better at getting deals than his wife? </u>

For this you use conditional probability.

You want to determine the probability of the response be " I am" given that the respondent is a "Husband".

Using conditional probability:

  • P ( "I am" / "Husband") = P ("I am" ∩ "Husband) / P("Husband")

  • P ("I am" ∩ "Husband) = 0.275 (from the intersection of the column "I am" and the row "Husband)

  • P("Husband") = 0.502 (from the total of the row "Husband")

  • P ("I am" ∩ "Husband) / P("Husband") = 0.275 / 0.502 = 0.548

<u>d. Given that the respondent is a wife, what is the probability that she feels she is better at getting deals than her husband?</u>

You want to determine the probability of the response being "I am" given that the respondent is a "Wife", for which you use again the formula for conditional probability:

  • P ("I am" / "Wife") = P ("I am" ∩ "Wife") / P ("Wife")

  • P ("I am" / "Wife") = 0.287 / 0.498

  • P ("I am" / "Wife") = 0.576

<u>e. Given a response "My spouse," is better at getting deals, what is the probability that the response came from a husband?</u>

You want to determine: P ("Husband" / "My spouse")

Using the formula of conditional probability:

  • P("Husband" / "My spouse") = P("Husband" ∩ "My spouse")/P("My spouse")

  • P("Husband" / "My spouse") = 0.126/0.236

  • P("Husband" / "My spouse") = 0.534

<u>f. Given a response "We are equal" what is the probability that the response came from a husband? What is the probability that the response came from a wife?</u>

<u>What is the probability that the response came from a husband?</u>

  • P("Husband" / "We are equal") = P("Husband" ∩ "We are equal" / P ("We are equal")

  • P("Husband" / "We are equal") = 0.101 / 0.502 = 0.201

<u>What is the probability that the response came from a wife:</u>

  • P("Wife") / "We are equal") = P("Wife" ∩ "We are equal") / P("We are equal")

  • P("Wife") / "We are equal") = 0.101 / 0.498 = 0.208
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