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lapo4ka [179]
3 years ago
12

Direct mail advertisers send solicitations​ ("junk mail") to thousands of potential customers in the hope that some will buy the

​ company's product. The response rate is usually quite low. Suppose a company wants to test the response to a new flyer and sends it to 1030 people randomly selected from their mailing list of over​ 200,000 people. They get orders from 103 of the recipients.
Required:
Create a 95% confidence interval for the percentage of people the company contacts who may buy something. (Show your work. Step by step)
Mathematics
1 answer:
harina [27]3 years ago
5 0

Answer:

The interval is (.0817, .118).

Step-by-step explanation:

Let's make this interval! The easy way is to go to STAT->TEST->A, 1-prop z-int, but I will show the long way.

<u>1. Conditions</u>

First we must check the conditions.

<em>Randomization condition: </em>The sample is given to be random, so we can assume independence.

<em>Success/failure condition: </em>Both np>10 and nq>10 must be met.

  • np = 1030(103/1030) = 103 ✓
  • nq = 1030(927/1030) = 927 ✓

<em>10% condition: </em>The sample cannot be greater than 10% of the population.

  • 10n < N, 10(1030) < 200000 ✓

All conditions are met, so we can use <u>a 1-proportion z-interval</u> to represent the data.

<u></u>

<u>2. Mechanics</u>

<u>Find </u>\hat{p}<u>, the sample proportion.</u>

103/1030 = .1

\hat{q}, then, the probability of not p, is 1 - .1 = .9

<u>Find z* (z star), the critical z-value.</u>

You can do this on your calculator using 2nd->VARS->3 (or you can memorize it - it's 1.96. Winky face.) This is called the invNorm function, that takes the left side area under the normal curve. But what do we plug in to the invNorm function?

invNorm(.975) = 1.96

<u>Plug values into the equation.</u>

\hat{p} ± z*\sqrt{\frac{\hat{p}\hat{q}}{n} }

.1 ± 1.96\sqrt{\frac{.1*.9}{1030} }

.1 ± 1.96(.00935)

.1 - .0183 = .0817

.1 + .0183 = .118

(.0817, .118)

<u>3. Conclusion</u>

Based on this sample, we are 95% confident that the proportion of people the company contacts who may buy something is between .0817 and .118. That isn't very likely, but maybe they'll make a little profit!

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An electrician charges $40 per visit, and $20 per hour of work. On a particular day, he made 3 visits and calculated that his av
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Answer:

  4 hours

Step-by-step explanation:

For three visits, the electrician earned $40 × 3 = $120 in "per-visit" charges. For working x hours, he earned 20x in "per-hour" charges. The total of these came to 50x:

  120 +20x = 50x

  120 = 30x . . . . . . . . subtract 20x

  4 = x . . . . . . . . . . . . . divide by 30

The electrician worked 4 hours that day.

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3 years ago
How many lines of symmetry does a regular polygon with 16 sides have? A. 2 B. 8 C. 32 D. 16
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Answer:

C. 32

Step-by-step explanation:

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N ∆ABC, if sin A = and tan A = , then what is cos A?
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Step-by-step explanation:

8 0
3 years ago
C) Parbati buys a mobile for Rs 6,300 and sells it to Laxmi at 15% profit. How much
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Answer:

Rs. 7245

Step-by-step explanation:

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Cost price  = Rs. 6300

Percentage profit  = 15%

Unknown:

Selling price = ?

Solution:

If profit is made on a trade, the selling price is higher than the cost price.

 Profit  = Selling price  - Cost price

To find the selling price simply;

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6 0
3 years ago
A random sample of n 1 = 249 people who live in a city were selected and 87 identified as a democrat. a random sample of n 2 = 1
kvasek [131]

Answer:

CI=\{-0.2941,-0.0337\}

Step-by-step explanation:

Assuming conditions are met, the formula for a confidence interval (CI) for the difference between two population proportions is \displaystyle CI=(\hat{p}_1-\hat{p}_2)\pm z^*\sqrt{\frac{\hat{p}_1(1-\hat{p}_1)}{n_1}+\frac{\hat{p}_2(1-\hat{p}_2)}{n_2} where \hat{p}_1 and n_1 are the sample proportion and sample size of the first sample, and \hat{p}_2 and n_2 are the sample proportion and sample size of the second sample.

We see that \hat{p}_1=\frac{87}{249}\approx0.3494 and \hat{p}_2=\frac{58}{113}\approx0.5133. We also know that a 98% confidence level corresponds to a critical value of z^*=2.33, so we can plug these values into the formula to get our desired confidence interval:

\displaystyle CI=(\hat{p}_1-\hat{p}_2)\pm z^*\sqrt{\frac{\hat{p}_1(1-\hat{p}_1)}{n_1}+\frac{\hat{p}_2(1-\hat{p}_2)}{n_2}}\\\\CI=\biggr(\frac{87}{249}-\frac{58}{113}\biggr)\pm 2.33\sqrt{\frac{\frac{87}{249}(1-\frac{87}{249})}{249}+\frac{\frac{58}{113}(1-\frac{58}{113})}{113}}\\\\CI=\{-0.2941,-0.0337\}

Hence, we are 98% confident that the true difference in the proportion of people that live in a city who identify as a democrat and the proportion of people that live in a rural area who identify as a democrat is contained within the interval {-0.2941,-0.0337}

The 98% confidence interval also suggests that it may be more likely that identified democrats in a rural area have a greater proportion than identified democrats in a city since the differences in the interval are less than 0.

5 0
2 years ago
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