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A statistic is an unbiased estimator of a parameter when

a. the statistic is calculated from a random sample.

b. in a single sample, the value of the statistic is equal to the value of the parameter.

c. in many samples, the values of the statistic are very close to the value of the

parameter.

d. in many samples, the values of the statistic are centered at the value of the parameter.

e. in many samples, the distribution of the statistic has a shape that is approximately

Normal.

Short Answer

Expert verified

The correct option is (d) in many samples, the values of the statistic are centered at the value of the parameter.

Step by step solution

01

 Step 1: Given information 

We have to find when a statistic is an unbiased parameter

02

Explanation for incorrect option(a)

The measurement is calculated from an irregular sample. That's not an imperative necessity in arrange to guarantee that measurement is unbiased.

03

Explanation for incorrect option(b)

In a single test, the esteem of the measurement is broken even with the esteem of the parameter. False, we require that in numerous tests the values of the measurement would be break even with the parameter

04

Explanation for incorrect option(c)

In numerous tests, the values of the measurement are exceptionally near to the esteem of the parameter. False, we require that in numerous tests the values of the measurement would be precisely break even with the parameter

05

Explanation for correct option(d)

In numerous tests, the values of the measurement are centered on the esteem of the parameter. True we have the two conditions fulfilled, centered at the parameter and the expected esteem is rise to the parameter.

Hence, (d) in many samples, the values of the statistic are centered at the value of the parameter is the correct answer.

06

Explanation for incorrect option(e)

In numerous tests, the dissemination of the measurement encompasses a shape that's around Normal. Not a select condition and not vital.

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Most popular questions from this chapter

Bias and variability The figure shows approximate sampling distributions of 4different

statistics intended to estimate the same parameter.




a. Which statistics are unbiased estimators? Justify your answer.

b. Which statistic does the best job of estimating the parameter? Explain your answer.

Bearings A production run of ball bearings is supposed to have a mean diameter of 2.5000centimeters (cm). An inspector chooses 100bearings at random from the run. These bearings have mean diameter 2.5009cm.

identify the population, the parameter, the sample, and the statistic.

The Gallup Poll has decided to increase the size of its random sample of voters from about 1500 people to about 4000 people right before an election. The poll is designed to estimate the proportion of voters who favor a new law banning smoking in public buildings. The effect of this increase is to

a. reduce the bias of the estimate.

b. increase the bias of the estimate.

c. reduce the variability of the estimate.

d. increase the variability of the estimate.

e. reduce the bias and variability of the estimate.

Really cold cabin The dotplot shows the results of taking 300SRSs of 10temperature readings from a Normal population with μ=50and σ=3and recording the sample minimum each time. Suppose that the minimum of an actual sample is 40°F. What would you conclude about the thermostat manufacturer’s claim? Explain your reasoning.

Even more tall girls, Refer to Exercises 12and 14. Suppose that the sample mean height of the twenty 16-year-old females is x=65.8inches. Would this sample mean provide convincing evidence that the average height of all 16-year-old females at this school is greater than 64inches? Explain your reasoning.

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