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ESTIMATION
Estimation is a mathematical technique for producing information about a population based on a sample of units from that population. Different sampling techniques require different estimation techniques.
Estimation allows you to derive measures of location, spread, and totals for the whole population. This and following pages will outline the estimation techniques for the mean and total of a population from a simple random sample only.
ESTIMATE OF POPULATION MEAN
For a simple random sample, the estimate of the population mean is the same as the mean of the sample:
where:
x stands for an observed value,
stands for the estimate of population mean,
stands for the sum of all observed x values in the sample, and
n stands for the number of observations in the sample.
NOTE:
Lower case x and n should be used if you are referring to a sample survey, and upper case X and N if referring to a population.
If the sample results have been summarised in a frequency table then the estimate for the population mean is again the same as the sample:
where:
x stands for an observed value,
stands for the estimate of the population mean,
xf stands for the sum of all xf values in the sample, and
f stands for the sum of the frequencies in the sample.
EXAMPLE
1. | 10 eggs were selected randomly from a set of 200 eggs. The weights were recorded as:
0.75, 0.70, 0.55, 0.50, 0.60, 0.65, 0.75, 0.65, 0.75 and 0.50 grams? |
What is the mean weight of the 200 eggs?
Using the formula on the previous page:
= 6.4 / 10
= 0.64 grams
ESTIMATE OF POPULATION TOTAL
For a simple random sample the estimate of population total is given by:
where:
x stands for an observed value,
stands for estimated population total,
x stands for sum of all observed x values in the sample,
n stands for number of observations in the sample, and
N stands for total number of observations in the population.
If sample results have been summarised in a frequency table then the estimate for population total is given by:
where:
x stands for an observed value,
stands for estimated population total,
xf stands for sum of all observed xf values in the sample,
f stands for sum of frequencies in the sample, and
N stands for total number of observations in the population.
BIAS IN ESTIMATION
There are a number of sources that can introduce bias into survey results: response errors, incorrect procedures and processing were discussed on pages 63-65. Bias can also be introduced if estimation is not appropriate to the sampling method used.
For example, in Exercise 3 below, a stratified random sample has been drawn from all capital cities. If the proportion of Labor supporters over all capital cities is estimated as:
total Labor supporters/total sample (531/1,220 — 43.5%)
the estimate would be biased.
The reason is that all units in the sample did not have the same chance of being selected. For example:
the chances of a person from Sydney being selected were about:
300/3,740,000 = 0.0000802
the chances of a person from Canberra being selected were about:
60/300,000 = 0.0002
Thus, the estimate would be biased toward Canberra preferences.
(Note: total population figures have been taken from the 1996 Census.)
EXERCISES
1. | | Give an example of a simple random sample and briefly describe why it is classed in this category. |
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2. | a) | If a company has a workforce of 2,700 people, and a sample of 300 people were to be systematically surveyed, what would the sampling interval be? |
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3. | b) | Choose a number at random as a starting point for the above sample. What would be the first 5 numbers in the sample? What would be the last 5 numbers in the sample? |
The response from a stratified sample of people (18 years and over) in capital cities in Australia to the question ‘Which political party would you prefer to be in power?’ follows:
| MELB. | ADEL. | PERTH | SYD. | BRIS. | HOB. | DAR. | CANB. |
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LABOR | 85 | 65 | 81 | 127 | 74 | 40 | 22 | 37 |
LIBERAL | 80 | 70 | 60 | 135 | 50 | 40 | 26 | 13 |
OTHER | 10 | 31 | 6 | 22 | 13 | 8 | 18 | 6 |
UNDECIDED | 25 | 14 | 13 | 16 | 13 | 12 | 4 | 4 |
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TOTAL | 200 | 180 | 160 | 300 | 150 | 100 | 70 | 60 |
| a) | In which city was the greatest percentage of people: |
| | i) in favour of Labor? |
| | ii) in favour of Liberal? |
| | iii) in favour of another political party? |
| | iv) undecided? |
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| b) | In which city was the least percentage of people: |
| | i) in favour of Labor? |
| | ii) in favour of Liberal? |
| | iii) in favour of another political party? |
| | iv) undecided? |
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| c) | Is it possible to estimate overall percentages for capital cities from the above table? |
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4. | | In a school, the number of students in each year level from kindergarten to Year 12 is as follows: |
| K | P | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
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Males | 9 | 8 | 9 | 9 | 13 | 20 | 23 | 28 | 78 | 74 | 69 | 71 | 60 | 48 |
Females | 6 | 8 | 11 | 10 | 13 | 18 | 35 | 34 | 63 | 62 | 61 | 88 | 70 | 56 |
Total | 15 | 16 | 20 | 19 | 26 | 38 | 58 | 62 | 141 | 136 | 130 | 159 | 130 | 104 |
K= Kindergarten, P= Pre-school
The school has been granted a sum of money to build a new library or gym. The Principal wishes to take into consideration the opinion of students as to whether they would prefer a library or a gym.
The Principal wants to ensure that a sample survey contains students from different year levels and sexes. To determine student numbers for each year level and sex, the Principal will assume each value is to be represented proportionally.
For example, to calculate male kindergarten student numbers in the sample the Principal would use this formula:
Once the number of students in each category has been determined, the students will be selected randomly.
| a) | What type of sampling technique is this called? |
| b) | If the Principal wishes to survey 200 students, how many students of each sex and in each year level should be surveyed? |
(Results should be rounded to the nearest whole number.)
Click here for answers
CLASS ACTIVITIES
1. | | Use one of the random sampling methods described to obtain a random sample from your class or year level. Use this sample to find out one or more of the following: |
| a) | average number of children in a family, |
| b) | type of transport used to get to school, |
| c) | number of students in favour of capital punishment, |
| d) | amount of pocket money received, |
| e) | type of pets kept, |
| f) | number of people in a family who have had tertiary education. |
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2. | | Obtain a list showing the name and gender of each student by year level in your school. Using the stratified sampling technique, survey 20% of the school’s population to find the students’ favourite subject. Use the strata of year level and gender. |
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