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LiRa [457]
2 years ago
15

The following are the hypotheses for a test of the claim that college graduation statue and cola preference are independent. H0:

College graduation status and cola preference are independent. H1: College graduation status and cola preference are dependent. If the test statistic: χ2 = 0.579 and the critical value is χ2 = 5.991, what is your conclusion about the null hypothesis and about the claim?
Mathematics
1 answer:
Shkiper50 [21]2 years ago
7 0

Answer:

\chi^2 = 0.579

And the critical value for the significance level used is:

\chi^2_{crit}= 5.991

Since the calculated value is less than the critical value we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the College graduation status and cola preference are independent

Step-by-step explanation:

For this case we want to test the following hypothesis:

Null hypothesis: College graduation status and cola preference are independent

Alternative hypothesis: College graduation status and cola preference are dependent

For this case we got a calculated statistic of:

\chi^2 = 0.579

And the critical value for the significance level used is:

\chi^2_{crit}= 5.991

Since the calculated value is less than the critical value we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the College graduation status and cola preference are independent

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Two different samples will be taken from the same population of test scores where the population mean and standard deviation are
Alenkinab [10]

Answer:

The sample consisting of 64 data values would give a greater precision.

Step-by-step explanation:

The width of a (1 - <em>α</em>)% confidence interval for population mean μ is:

\text{Width}=2\cdot z_{\alpha/2}\cdot \frac{\sigma}{\sqrt{n}}

So, from the formula of the width of the interval it is clear that the width is inversely proportion to the sample size (<em>n</em>).

That is, as the sample size increases the interval width would decrease and as the sample size decreases the interval width would increase.

Here it is provided that two different samples will be taken from the same population of test scores and a 95% confidence interval will be constructed for each sample to estimate the population mean.

The two sample sizes are:

<em>n</em>₁ = 25

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The 95% confidence interval constructed using the sample of 64 values will have a smaller width than the the one constructed using the sample of 25 values.

Width for n = 25:

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\text{Width}=2\cdot z_{\alpha/2}\cdot \frac{\sigma}{\sqrt{64}}=\frac{1}{8}\cdot [2\cdot z_{\alpha/2}\cdot \sigma]

Thus, the sample consisting of 64 data values would give a greater precision

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1 year ago
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