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Which of the following statistics are unbiased estimators of population​ parameters?

  1. Sample proportion used to estimate a population proportion.
  2. Sample mean used to estimate a population mean.
  3. Sample variance used to estimate a population variance.
  4. All of the above.

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Jean Keeling
Jean KeelingLv2
24 Jan 2020
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Related textbook solutions

Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

6. As the test statistic becomes larger, the p-value

(a) gets smaller

(b) becomes larger 

(c) stays the same, since the sample size has not been changed

(d) becomes negative.

 

7. To describe the sampling distribution of the sample proportion, we use

(a) The sample proportion 

(b) The population proportion 

(c) The population mean

(d) The population mean

 

8. When small samples are used to estimate a population mean, in cases where the population standard deviation is unknown and the original distribution is normal:

(a) There always will be a large amount of sampling error.

(b) the t-distribution must be used to obtain the critical value.

(c) the resulting margin of error for a confidence interval estimate will tend to be fairly small.

(d) the z distribution must be used to obtain the critical value.

 

 

In inferential statistics, we calculate statistics of sample data to ______________.

A. estimate unknown population parameters and conduct tests about unknown population parameters

B. estimate unknown population parameters

C. None of the Answers

D. conduct tests about unknown population parameters

When 2 births are randomly selected, the sample space for genders is bb, bg, gb, and gg. Assume that those 4 outcomes are equally likely. Construct a table that describes the sampling distribution of the sample proportion of girls from 2 births. Does the mean of the sample proportions equal the proportion of girls in 2 births? Does the result suggest that a sample proportion is an unbiased estimator of a population proportion?

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