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My name is Ann [436]
3 years ago
13

According to a 2009 Reader's Digest article, people throw away approximately 13% of what they buy at the grocery store. Assume t

his is the true proportion and you plan to randomly survey 101 grocery shoppers to investigate their behavior. What is the probability that the sample proportion exceeds 0.16?
Mathematics
1 answer:
OverLord2011 [107]3 years ago
4 0

Answer:

The probability that the sample proportion exceeds 0.16 is 0.2061.

Step-by-step explanation:

We are given that according to a 2009 Reader's Digest article, people throw away approximately 13% of what they buy at the grocery store.

You plan to randomly survey 101 grocery shoppers to investigate their behavior.

Let \hat p = sample proportion

The z-score probability distribution for the sample proportion is given by;

                               Z  =  \frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } }  ~ N(0,1)

where, \hat p = sample population = 0.16

           n = sample of grocery shoppers = 101

Now, the probability that the sample proportion exceeds 0.16 is given by = P(\hat p > 0.16)

  P(\hat p > 0.16) = P( \frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } } > \frac{0.16-0.13}{\sqrt{\frac{0.16(1-0.16)}{101} } } ) = P(Z > 0.82) = 1 - P(Z \leq 0.82)

                                                               = 1 - 0.7939 = <u>0.2061</u>

The above probability is calculated by looking at the value of x = 0.82 in the z table which has an area of 0.7939.

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Read 2 more answers
The following data give the estimated prices of a 6-ounce can or a 7.06-ounce pouch of water-packed tuna for 14 different brands
Vikentia [17]

Answer:

a) Range = 1.39

b) the sample variance is 0.1597

c) the sample standard deviation is 0.3996

Step-by-step explanation:

Given the data in the question;

a) Find the range.

To determine the range, we simple subtract the smallest value from the largest value. i.e

Range = largest value - smallest value

from data set; our smallest is 0.53 while our largest value is 1.92

so

Range = 1.92 - 0.53 = 1.39

b) Find the sample variance.

To determine our variance, we use the following formula;

∑(X_{i} - x_{bar})² / n - 1 = [ ∑X_{i}²/n-1 ] - [ \frac{n}{n-1}(x_{bar})²]

where x_{bar} =  ∑X_{i}/n

n is sample size = 14 so lets calculate ∑X_{i}

∑X_{i} = 0.99 + 1.92 + 1.23 + 0.85 + 0.65 + 0.53 + 1.41  + 1.12 + 0.63 + 0.67 + 0.69 + 0.60 + 0.60 + 0.66

∑X_{i}  =  12.55    

∑X_{i}² = 0.99² + 1.92² + 1.23² + 0.85² + 0.65² + 0.53² + 1.41²  + 1.12² + 0.63² + 0.67² + 0.69² + 0.60² + 0.60² + 0.66²

∑X_{i}² = 13.3253

so

our  x_{bar} =  ∑X_{i}/n = 12.55 / 14 = 0.8964

so our Variance  will be;

= [ ∑X_{i}²/n-1 ] - [ \frac{n}{n-1}(x_{bar})²]

= [ 13.3253 / 14-1 ] - [ \frac{14}{14-1} (0.8964)²]

= 1.025 - 0.8653

= 0.1597

Therefore, the sample variance is 0.1597

c) Find the sample standard deviation.

we know that standard deviation is the square root of variance;

standard deviation = √Variance

standard deviation = √0.1597

standard deviation = 0.3996

Therefore, the sample standard deviation is 0.3996

7 0
3 years ago
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