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IceJOKER [234]
3 years ago
15

A study showed that 69% of supermarket shoppers believe supermarket brands to be as good as national name brands. To investigate

whether this result applies to its own product, the manufacturer of a national name-brand ketchup asked a sample of shoppers whether they believed that supermarket ketchup was as good as the national brand ketchup.
a. Formulate the hypotheses that could be used to determine whether the percentage of supermarket shoppers who believe that the supermarket ketchup was as good as the national brand ketchup differed from 69%.
b. If a sample of 100 shoppers showed 56 stating that the supermarket brand was as good as the national brand, what is the p-value (to 4 decimals)?
c. At α = .05, what is your conclusion?
d. Should the national brand ketchup manufacturer be pleased with this conclusion?
Mathematics
1 answer:
Valentin [98]3 years ago
6 0

Answer:

We conclude that supermarket ketchup was not as good as the national brand ketchup.

Step-by-step explanation:

We are given the following in the question:

Sample size, n = 100

p = 69% = 0.69

Alpha, α = 0.05

Number of stating that the supermarket brand was as good as the national brand , x = 56

a) First, we design the null and the alternate hypothesis

H_{0}: p = 0.69\\H_A: p \neq 0.69

This is a two-tailed test.  

b) Formula:

\hat{p} = \dfrac{x}{n} = \dfrac{56}{100} = 0.56

z = \dfrac{\hat{p}-p}{\sqrt{\dfrac{p(1-p)}{n}}}

Putting the values, we get,

z = \displaystyle\frac{0.56-0.69}{\sqrt{\frac{0.69(1-0.69)}{100}}} = -2.810

Now, we calculate the p-value from the table.

P-value =  0.0049

c) Since the p-value is lower than the significance level, we fail to accept the null and reject it.

Thus, we conclude that supermarket ketchup was not as good as the national brand ketchup.

d) It need to be tested further whether the supermarket brand was worse than the national brand or better than the national brand.

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Answer:

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And for this case we know this condition:

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Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

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Solution to the problem

For this case if we define the random variable of interest X and we know that this random variable follows a normal distribution:

X \sim N (\mu ,\sigma)

And for this case we know this condition:

P(\mu-2\sigma

By the complement rule we know that:

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But since the distribution is symmetrical we know that:

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