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BAC2 ss · Mathematics
Statistics · Sampling

Point estimation: estimators, bias and the sample variance with n−1

We do not know the true mean monthly leisure spending of all university students in Spain, but we can measure it in a sample of $100$ students. Does that sample number "count" as an estimate of the true mean? Which formula should we use so that it is not systematically off target? That is point estimation.

Before you start, make sure you know: One-variable descriptive statistics (1st Bachillerato)
Before you start, make sure you know: The normal distribution (1st Bachillerato)

What a point estimator is

Flow diagram illustrating point estimation: from the data in a sample, an estimator is calculated to approximate unknown population parameters. Sample (observed data) Estimator x̄, p̂… approximates μ, p… (unknown)
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To estimate the mean height of students in $2.º$ Baccalaureate in a city, a random sample of $5$ students is taken, with the following results in centimetres: $165$,…

To estimate the mean height of students in $2.º$ Baccalaureate in a city, a random sample of $5$ students is taken, with the following results in centimetres: $165$, $170$, $172$, $168$, $175$.

  • a) Calculate the point estimate of the population mean.

  • b) Explain why this value is only an estimate and not the true mean.

Solve
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In a survey of $300$ randomly chosen students, $87$ state that they cycle to school. a) What is the point estimate of the population proportion of students who cycle to…

In a survey of $300$ randomly chosen students, $87$ state that they cycle to school.

  • a) What is the point estimate of the population proportion of students who cycle to school? Calculate it.

  • b) Express the result as a percentage and interpret it.

Solve

Unbiased estimator

The same parameter can be estimated in several ways: with the mean, with the median, with the midpoint between the minimum and the maximum... Not all of them are equally good.

Visual comparison between an unbiased estimator, centred on the true population parameter, and a biased estimator, systematically shifted away from the true value. unbiased: centred on the parameter biased: systematically shifted true parameter
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True or false, reasoning your answer: "The sample mean is an unbiased estimator of the population mean, meaning that if we were to take many samples of the same size and…

True or false, reasoning your answer: "The sample mean is an unbiased estimator of the population mean, meaning that if we were to take many samples of the same size and calculate their means, the average of all of them would equal the population mean."

Solve
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A company wants to estimate the mean of a population and an analyst proposes taking the maximum value of the sample as an "estimator". a) Consider the population…

A company wants to estimate the mean of a population and an analyst proposes taking the maximum value of the sample as an "estimator".

  • a) Consider the population consisting of the values $\{2, 4, 6\}$ and all samples of size $2$ with replacement. Calculate the population mean and the average of the maximums of all possible samples.

  • b) In light of the result, is that estimator unbiased? Explain what the bias of an estimator is based on your calculations.

Solve
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Consider the population consisting of the five values $\{1, 2, 3, 4, 5\}$. a) Calculate the population mean $\mu$. b) Write down all samples of size $2$ without…

Consider the population consisting of the five values $\{1, 2, 3, 4, 5\}$.

  • a) Calculate the population mean $\mu$.

  • b) Write down all samples of size $2$ without replacement and without regard to order, and calculate the mean of each one.

  • c) Calculate the average of these sample means and check that it equals $\mu$. Which property of the "sample mean" estimator does this result illustrate?

Solve

The unbiased sample variance: why divide by $n-1$

When we estimate the variability of a population from a sample, there is a surprise: dividing by $n$ (as in the "ordinary" variance) gives a biased estimator.

Visual comparison of the calculation of the sample variance dividing by n versus the unbiased sample variance dividing by n-1. data: 4, 6, 5, 9 → x̄=6 s²=Σ(xᵢ−x̄)²/n → divide by 4 (smaller) ŝ²=Σ(xᵢ−x̄)²/(n−1) → divide by 3 (unbiased)
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A random sample from a population yielded the values $4$, $6$, $5$ and $9$. a) Calculate the sample mean. b) Calculate the sample variance (dividing by $n$) and the…

A random sample from a population yielded the values $4$, $6$, $5$ and $9$.

  • a) Calculate the sample mean.

  • b) Calculate the sample variance (dividing by $n$) and the unbiased sample variance (dividing by $n - 1$).

  • c) Which of the two is used as an unbiased estimator of the population variance? What does "unbiased" mean?

Solve
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The full charging times (in minutes) of $8$ mobile phones of the same brand have been measured: $74$, $81$, $69$, $78$, $85$, $72$, $77$, $80$. a) Estimate the mean…

The full charging times (in minutes) of $8$ mobile phones of the same brand have been measured: $74$, $81$, $69$, $78$, $85$, $72$, $77$, $80$.

  • a) Estimate the mean charging time for this model using an unbiased estimator.

  • b) Estimate its variance using an unbiased estimator (unbiased sample variance).

  • c) Also calculate the unbiased sample standard deviation and interpret both results.

Solve
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A property portal takes a sample of $6$ advertisements for rooms to rent in a neighbourhood, with the following monthly prices in euros: $450$, $520$, $480$, $510$,…

A property portal takes a sample of $6$ advertisements for rooms to rent in a neighbourhood, with the following monthly prices in euros: $450$, $520$, $480$, $510$, $465$, $495$.

  • a) Estimate the mean price of the neighbourhood using an unbiased estimator.

  • b) Estimate the variability of the prices by calculating the unbiased sample variance and the unbiased sample standard deviation.

  • c) Explain, using the numbers from this exercise, the difference between dividing by $n$ and by $n - 1$, and why the unbiased estimation uses $n - 1$.

Solve

Estimation error and efficiency

Distinguish between the actual error (estimate minus parameter, normally unknown), the standard error (the variability of the estimator) and the margin of an interval at a given confidence level. Among several unbiased estimators, we prefer the one that varies least: the most efficient.

Representation of the margin of error around a point estimate, marking the interval centred on the estimator. n=40 draws n=400 draws (×10) error ÷ √10
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In a random sample of $500$ customers of a supermarket chain, $210$ state that they use the chain's application to do their shopping. a) Estimate the population…

In a random sample of $500$ customers of a supermarket chain, $210$ state that they use the chain's application to do their shopping.

  • a) Estimate the population proportion of customers who use the application.

  • b) Calculate the maximum error of the estimate with a confidence level of $95\ \%$, using $E = 1,96 \cdot \sqrt{\frac{\hat{p} \cdot (1 - \hat{p})}{n}}$.

  • c) Interpret the result: between which values does the true proportion lie, with that level of confidence?

Solve
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To estimate the mean $\mu$ of a normal distribution, three estimators based on a random sample are proposed: the sample mean, the sample median and the midpoint between…

To estimate the mean $\mu$ of a normal distribution, three estimators based on a random sample are proposed: the sample mean, the sample median and the midpoint between the minimum and the maximum of the sample.

  • a) Explain what it means for an estimator to be unbiased and discuss whether all three are expected to be unbiased in a symmetric distribution such as the normal.

  • b) Explain what the efficiency of an estimator is and reason which of the three will, in general, be less efficient. Why is the sample mean usually preferred?

Solve
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From an urn containing an unknown proportion $p$ of red balls, $40$ balls are drawn with replacement, and $14$ are red. a) Give the point estimator of $p$ and its value.…

From an urn containing an unknown proportion $p$ of red balls, $40$ balls are drawn with replacement, and $14$ are red.

  • a) Give the point estimator of $p$ and its value.

  • b) Reason why, if instead of $40$ draws $400$ were made, the standard error of the estimate would be divided by approximately $\sqrt{10}$. Use the formula for the error $E = z_{\alpha/2} \cdot \sqrt{\frac{\hat{p} \cdot (1 - \hat{p})}{n}}$.

  • c) What is the relationship between this property and the law of large numbers?

Solve

Back to the start: Yes, it "counts": the sample mean $\bar{x} = \frac{\sum x_i}{100}$ is the point estimate of the true mean $\mu$, and since it is an unbiased estimator we know that its expected value is not systematically off target.

Summary

See all the exercises in this section