COLLECTION OF DATA
Pilot Survey
- After the questionnaire is ready, it is desirable to carry a try-out with a diminutive group, known as Pilot Survey or Pre-Testing of the questionnaire.
- The pilot survey serves to give a preliminary impression of the survey.
- It helps to pretest the questionnaire and know the lapses and drawbacks.
- It also aids to assess the appropriateness of questions, the accuracy of guidance, the administration of enumerators, and the expense and time required in the actual survey.
Census
- A survey, which encompasses every component of the population, is apprehended as Census or the Method of Complete Enumeration.
- The primary feature of this approach is that this comprises every individual unit in the whole population.
Merits
- Reliable and accurate
- Less biased
- Extensive information
- Study of diverse characteristic
- Study of complex investigation
- Indirect investigation
(b) Demerits
- Costly
- Large manpower
- Not suitable for large investigation
Sample Survey
- A sample refers to a section of the population from which information has to be taken. A good sample (representative sample) is usually short and competent in giving reasonably accurate information about the population at a lower cost and in less time.
- Most of the surveys are sample surveys and are preferable in statistics because of several reasons.
- A sample can give rationally secure and authentic information at a lower cost and in less time.
Merits
- Economical
- Time saving
- Identification of error
- Large investigation
- Administrative convenience
- More scientific
(b) Demerits
- Partial
- Wrong conclusions
- Difficulty in selecting representative sample
- Difficulty in framing a sample
- Specialised knowledge
- Now the question is how do you do the sampling? There are two main types of sampling:
- Random Sampling
- Non-random Sampling
Random Sampling
- It is also known as the lottery method.
- Random sampling is where the specific units from the population (samples) are randomly selected.
- In random sampling, each person has an equal possibility of being chosen, and the person who is selected is the same as the one who is not selected.
- Random number tables are generated to ensure an equal chance of selection of every single unit in the population.
- They are accessible either in an issued form or can be generated by employing relevant software packages.
Non-random sampling
- In this method, units of the population don’t have equal chances of being selected.
- The convenience or interpretation of the investigator plays a crucial role in the adoption of the sample.
- They are chiefly selected based on belief, purpose, ease, or quota and are non-random samples.
Sampling errors
- Sampling error applies to the variations between the sample estimate and the actual value.
- It is the error that transpires when you observe the sample taken from the population.
- The point of differentiation between the actual parameter of the population and its estimate is known as sampling error.
Non-sampling errors
Non-sampling errors are more consequential than sampling errors. Sampling error can be minimized by taking a larger sample, on the other hand, it is difficult to minimize non-sampling error. Even a Census can carry non-sampling errors.
Some of the non-sampling errors are:
- Errors in Data Acquisition: This type of error stems from recording inaccurate responses.
- Non-Response Errors: Non-response happens if an interviewer is incapable to contact a person listed in the sample or a person from the sample declined to respond. In this case, the sample research may not be representative.
- Sampling Bias: Sampling bias happens when the sampling plan is such that some portion of the target population could not possibly be incorporated into the sample.
Census of India and NSSO
The census of India is a very important body of our country and is an important part in the chapter class 11 collection, organisation and presentation of data.
- The Census of India and the National Sample Survey Organisation (NSSO), are two significant firms at the national level, which gather, manner, and tabulate data.
- The Census of India produces the most comprehensive and continuous demographic record of the population.
- The NSSO was established by the Government of India to conduct nationwide surveys on socio-economic issues.
- NSSO gives periodic measures of education, school enrolment, utilization of educational aids, employment, unemployment, manufacturing, and service sector enterprises, morbidity, maternity, child care, utilization of the public distribution system, etc.
1. Frame at least four appropriate multiple-choice options for following questions:
(a) Colour
(b) Price
(c) Brand
(d) Quality of cloth
(ii) How often do you use computers?
(b) 6 times a week
(c) 4 times a week
(d) 2 times a week
(iii) Which of the following newspaper/s do you read regularly?
Ans.
(a) The Times o India
(b) The Hindu
(c) Indian Express
(d) Any other
(iv) Rise in the price of petrol is justified.
(d) None of the above
(a) Less than Rs 10,000
(b) Rs 10,000 to Rs 20,000
(c) Rs 20,000 to Rs 30,000
(d) More than Rs 30,000
2. Frame five two-way questions (with 'Yes' or 'No').
Answer
(i) Do you own car?
(ii) Do you smoke?
(iii) Do you own two-wheeler?
(iv) Have you visited any foreign country?
(v) Are you satisfied with your present income?
Q3. State whether the following statement are true or false.
- There are many sources of data.
- Telephone survey is the most suitable method of collecting data, when the population is literate and spread over a large area.
- Data collected by investigator is called the secondary data.
- There is a certain bias involved in the nonrandom selection of samples.
- Non-sampling errors can be minimised by taking large samples.
Ans.
- False. There are generally two sources of data, i.e., Primary and Secondary.
- False. Mailing questionnaires will be more suitable because the population is literate. Telephonic survey will be more most
suitable in case when the population is illiterate population and spread over a large geographical area. - False. Investigator can gather the data by conducting an investigation or enquiry. Such data are known as primary data, as they are collected for the first time.
- True. When all the units of the population do not have an equal chance of being selected then it is called as non-random sampling method. This method involves personal biasness of the investigator.
- False. It is hard to minimise non-sampling error even by taking large samples as they include Sampling bias, Non-Response Errors, and Errors in Data Acquisition.
4. What do you think about the following questions. Do you find any problem with these questions? Describe.
- How far do you live from the closest market?
- If plastic bags are only 5 per cent of our garbage, should it be banned?
- Wouldn’t you be opposed to increase in price of petrol?
- Do you agree with the use of chemical fertilizers?
- Do you use fertilisers in your fields?
- What is the yield per hectare in your field?
Ans.
- This question is vague. People find difficulty in answering this question due to the different measures of distance such as yards, kilometers, meters, yards etc. It should be specific like how many kilometers is your home away from the closest market?
- Less than 4 km
- Between 4-8 km
- More than 8 km
- This is a prominent question, that gives a clue about how the respondent will answer. It can also be framed as Do you think plastic bags should be banned in our country? (Yes/No)
- This question contains two negatives words that may confuse the respondents and may lead to biased response. It must be framed as Would you oppose the rise in the price of petrol?
The order of questions (iv) (v) (vi) is incorrect. The series of questions must be from general to specific. The correct order is:- What is the yield per hectare in your field?
- Do you use fertilisers in your fields?
- Do you agree with the use of chemical fertilisers?
5. You want to research on the popularity of Vegetable Atta Noodles among children. Design a suitable questionnaire for collecting this information.
Ans. Questionnaire
Name ....................
Age ....................
Address ....................
....................
....................
Gender: Male □ Female □
- Do you eat noodles?
(a) Yes □
(b) No □ - Do you love noodles more than any other snacks?
(a) Yes □
(b) No □ - How many packets of noodles do you consume in a month?
(a) Less than 2 packets □
(b) 3-5 packets □
(c) 5-8 packets □
(d) More than 8 packets □ - Do you choose atta noodles over maida noodles?
(a) Yes □
(b) No □ - Do you like vegetables in your noodles?
(a) Yes □
(b) No □ - Do you think more veggies need to be added in vegetable atta noodles?
(a) Yes □
(b) No □ - According to you, which vegetables should be added in vegetable atta noodles?
…………………………………………………......... - Do you think it should be spicier?
(a) Yes □
(b) No □ - When will you prefer to eat vegetable atta noodles?
(a) In breakfast □
(b) In lunch □
(c) As evening snacks □
(d) In dinner □ - Do your parents like vegetable atta noodles too?
(a) Yes □
(b) No □
6. In a village of 200 farms, a study was conducted to find the cropping pattern. Out of the 50 farms surveyed, 50% grew only wheat. What is the population and the sample size?
Ans. The population in statistics also called as universe which means sum total of all the items under study. So, In this case, the population is 200 farms in the village.
A sample means a small portion of the population or universe which is considered as the exact representation of the population. Here, the sample size is 50 farms.
7. Give two examples each of sample, population and variable.
Ans. Example 1: A study was conducted to know the average height of students of class nineth in Karnal. The total number of students in class nineth was 4560. Out of these, 250 students were selected randomly and their height was recorded.
So, here
- Population is equal to the number of students of class nineth in Karnal, i.e., 4560.
- Sample is equal to the students selected randomly for recording the height, i.e., 250.
- Variable is the height of the students.
Example 2: A person suffering from fatigue and weakness was recommended by the doctor to do a blood test for detecting the disease of anaemia. The pathologist took 2.5 ml of his blood and tested the haemoglobin level.
So, here
- Population is equal to the total amount of blood present in the person’s body.
- Sample is equal to the amount of blood used to check the haemoglobin level, i.e., 2.5 ml.
- Variable is the haemoglobin in the sample.
8. Which of the following methods give better results and why?
(a) Census
(b) Sample
Ans. (b) Census is better as it deals with all the units of population and thus, provides accurate results as compared to sampling. But census method is very expensive and time consuming. Therefore, sampling method is much better due to following reasons:
- Time Saving: Huge amount of cost in terms of time, money and efforts are saved.
- Economical: Sampling deals with the study of only a part of population and thus reduces the cost of conducting survey when compared to census method.
- Lesser Effort: It involves lesser effort of the investigator than that which is required in case of census.
- Considerable Accuracy: Results generated from sampling may not be as accurate and reliable as in case of census method but the level of accuracy of these results can be recognised via statistical tests of significance and thus can be applied to the whole population in general.
9. Which of the following errors is more serious and why?
(a) Sampling error
(b) Non-sampling error
Ans. (a) Sampling error is the difference between the actual value of a population characteristic and sample estimate. This type of error arises when investigator select the sample from the population is not free from biasness. It can be reduced by increasing the sample size.
(b) Non-sampling errors are more severe than sampling errors as a sampling error can be minimised by taking large samples but it is difficult to minimise non-sampling error, even by taking a larger sample. Even a Census method can contain non-sampling errors. Non-sampling errors contains errors in data procurement, sampling bias and non-response errors.
10. Suppose there are 10 students in your class. You want to select three out of them. How many samples are possible?
Ans. Population size is N = 10 students, and sample size is n = 3 students.
Number of samples possible can be computed as follows:
Number of samples
11. Discuss how you would use the lottery method to select 3 students out of 10 in your class?
Ans. A random sample of 3 students can be selected from 10 using lottery method. In this, the names of all the ten students of the class are written on ten slips of paper of equal size and are folded in a same manner. After folding, all slips are mixed well and after that 3 slips are drawn at random so that each student will get an equal chance of being selected.
12. Does the lottery method always give you a random sample? Explain.
Ans. Lottery method always gives a random sample if it is done without any biasness. If the chits are prepared appropriately and drawn out one by one so that all the chits have equal chance of being selected in the sample, it will certainly give a random sample. However, if the clips are not of same size and then, the selection will be biased.
Likewise, if the same number is written on more than one chit and if some number is omitted then also the chances of selection of several units in the sample will be unequal. In such cases, lottery method will not be able to give random sample.
13. Explain the procedure for selecting a random sample of 3 students out of 10 in your class by using random number tables.
Ans. Random number tables have been developed to assure equal probability of selecting the sample units from the population based on the listed serial number. They are presented either in a published form or can be produced by using suitable software packages.
The process of selecting a random sample of 3 students out of 10 in a class by using random number tables is as follows:
- Allocate a particular number from 1 to 10 to all the 10 students.
- Here, the largest number is 10 which is a two digit number and thus, one refer two digit random numbers.
- He/she can start using the table from anywhere, that is, from any page, point, row, or column and choose the first number randomly. They need to choose a sample of 3 students out of 10 students.
- They will select two more numbers from the table as per the sequence. They will avoid the random numbers which are greater than 10 as there is no number greater than 10. Therefore, the 3 selected students are with serial numbers.
14. Do samples provide better results than surveys? Give reasons for your answer.
Ans. A survey that comprises of every element of the population is called as Census. It is also called as the Method of Complete Enumeration. In contrast, when only a part of the population is selected and studies then it is known as sampling.
Census is better as it deals with all the units of population and thus, provides accurate results as compared to sampling. But census method is very expensive and time consuming. Therefore, sampling method is much better due to following reasons:
- Time Saving: Huge amount of cost in terms of time, money and efforts are saved.
- Economical: Sampling deals with the study of only a part of population
- and thus reduces the cost of conducting survey when compared to census method.
- Lesser Effort: It involves lesser effort of the investigator than that which is required in case of census.
- Accuracy: Results generated from sampling may not be as accurate and reliable as in case of census method but the level of accuracy of these results can be recognised via statistical tests of significance and thus can be applied to the whole population in general.
- Inappropriateness of Census: In case where the population is infinite in nature, then in that case, it is difficult to use census method and thus sampling method is appropriate to use. For example, a person cannot burn all the pieces of coal just to know their calorific value, only samples can be selected for testing.
(a) Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of Assertion (A).
(b) Both Assertion (A) and Reason (R) are true and Reason (R) is not the correct explanation of Assertion (A).
(c) Assertion (A) is true but Reason (R) is false. (d) Assertion (A) is false but Reason (R) is true.
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