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The null hypothesis that the mean daily caloric intake in the adult population of a rural county is 1800 calories is being tested. A sample of 400 had a mean of 1785 and a standard deviation of 240. Use α = 0.10.
a) What is your conclusion?
b) What is the p-value? Explain, in your own words, in this context.
c) Find a 95% confidence interval for the mean daily caloric intake. Interpret this interval.
d) What is the difference between a chosen level of significance and the observed level of significance? Explain.
e) Based on the answer to part b), can you conclude that there is a 95% chance that the true mean daily caloric intake is 1800 calories? Explain?
f) What is meant by an unbiased estimator in this context and what is your unbiased estimate?
g) Does sample size play any role in estimation? Explain clearly.
Verified Expert
This paper is about hypothesis testing in Statistics. Hypothesis testing is a statistical step by step way to determine if there is enough evidence to reject the null hypothesis. This paper shows calculations on questions relating to hypothesis testing. The calculations involve calculation using z test and t test. The z test involves when the population variance or standard population is known and the sample size is more than 30. The t test is when the sample size is less than 30 or when the variance or standard deviation is unknown. This t test also involves the degrees of freedom when n-1 is calculated. Both test requires the z or t critical values to be read from the normal and t tables respectively.
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