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Collection and Classification  of Data Slide 1 Collection and Classification  of Data Slide 2 Collection and Classification  of Data Slide 3 Collection and Classification  of Data Slide 4 Collection and Classification  of Data Slide 5 Collection and Classification  of Data Slide 6 Collection and Classification  of Data Slide 7 Collection and Classification  of Data Slide 8 Collection and Classification  of Data Slide 9 Collection and Classification  of Data Slide 10 Collection and Classification  of Data Slide 11 Collection and Classification  of Data Slide 12 Collection and Classification  of Data Slide 13 Collection and Classification  of Data Slide 14 Collection and Classification  of Data Slide 15 Collection and Classification  of Data Slide 16 Collection and Classification  of Data Slide 17 Collection and Classification  of Data Slide 18 Collection and Classification  of Data Slide 19 Collection and Classification  of Data Slide 20 Collection and Classification  of Data Slide 21 Collection and Classification  of Data Slide 22 Collection and Classification  of Data Slide 23
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Collection and Classification of Data - Primary and secondary data , Classification of data, frequency array and frequency distribution

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Collection and Classification of Data

  1. 1. Suresh Babu G Assistant Professor CTE CPAS Paippad, Kottayam Collection and Classification of Data
  2. 2. Collection of Data Primary Data Secondary Data Data are collected from two sources Sources of Data Date is the collection of facts or information from which conclusion may be drawn
  3. 3. Primary Data • The enumerator (person who collects the data) may collect the data by conducting an enquiry or an investigation. Such data are called primary data. • It is also known as first hand data. • Example : A teacher conduct a test and collect data as mark.
  4. 4. Secondary Data • The data have been collected and processed (scrutinized and tabulated) by some other agency are called secondary data. • Sources of secondary data are government reports, documents, newspapers, magazine etc.. • Example – teacher collect data from anecdotal records.
  5. 5. Mode of Data Collection • Personal interviews – Investigator conducts face to face interviews with the respondents. • Mailing Questionnaire – sending questionnaire through mail with a request to complete and return it in the given date. • Telephone Interviews – investigator asks questions over the telephone. Personal interviews Mailing Questionnaire Telephone Interviews
  6. 6. Mode of Data Collection
  7. 7. Collection of Primary Data • Census or Complete Enumeration Method – A survey which includes every element of the population. • Sampling Method – Here a section or group of the population is taken for study.
  8. 8. Types of Sampling • Random Sampling – individual units from the population are selected at random. In random sampling every individual has an equal chance of being selected. • Non-Random Sampling – All the units of the population do not have an equal chance of being selected. Types of Sampling
  9. 9. Classification of Data • Chronological Classification – classification based on time such as years, months etc. • Spatial Classification – classification based on geographical locations such as countries, states, districts etc. • Quantitative Classification – classification of data based on quantity like height, weight, age etc. • Qualitative Classification – classification of data based on attributes or qualities such as religion, gender, literacy etc.
  10. 10. Grouped and Ungrouped Data  Ungrouped Data : The data obtained in original form are called raw data or ungrouped data. Example : Marks obtained by 10 students in a class in an examination is; 25, 8, 37, 16, 45, 40, 29, 12, 42, 14.  Any arrangement of ungrouped data in ascending or descending order of magnitude is called an array or called discrete series.
  11. 11. Marks obtained a test of maximum score of 5 by 20 students are given make a frequency array. 1, 2, 2, 1, 3, 4, 5, 5, 3, 2, 2, 3, 4, 3, 4, 1, 3, 3, 4, 4 Marks Tally No of students 1 lll 3 2 llll 4 3 llll l 6 4 llll 5 5 ll 2 Total 20 Frequency Array
  12. 12. • Grouped Data (Continuous series) – To put the data in a more condensed form, we make groups of suitable size, and mention the frequency of each group. Such table is called grouped frequency distribution table. Frequency Distribution Table Marks obtained a test of maximum score of 25 by 20 students are given make a frequency distribution table. 24, 1, 10, 21, 20, 4, 16, 5, 14, 2, 13, 20, 11, 8, 15, 9, 10, 17, 19, 22
  13. 13. Steps 1. Find the range (R) R = Highest value - Lowest value Here R = 24 – 1 = 23 2. Estimate number of class or intervals k K = n where n number of observations Note : If the resulting value is fractional, then we take the next higher integer. K = 20 = 5
  14. 14. 3. Estimate the class width c of each interval C = R/k Note : Round off the answer to the same number of decimal places that the observations have. C = 23/5 = 4.6 = 5
  15. 15. 4. List the lower and upper class limits of the fist interval. 5. List all succeeding lower and upper class limits by adding the class with c to the lower limit of the first class interval. The upper class limit of the first interval should be the number before the lower class interval of the second interval. Class interval (Class Mark) 0 – 5 5 – 10 10 – 15 15 – 20 20 - 25
  16. 16. 6. From the data, tally the observations according to the interval which it belongs to. Summarize the tallies in a column for the frequencies. Class Mark Tally Frequency 0 – 5 lll 3 5 – 10 lll 3 10 – 15 llll 5 15 – 20 llll 4 20 - 25 llll 5 Total 20
  17. 17. 7. Compute the class marks and class boundaries Class Mark = (lower class limit + Upper class limit) ÷ 2 Class Mark Tally Frequency Class mark 0 – 5 lll 3 2.5 5 – 10 lll 3 7.5 10 – 15 llll 5 12.5 15 – 20 llll 4 17.5 20 - 25 llll 5 22.5 Total 20
  18. 18. Conversion of Inclusive into Exclusive Lower limit – 0.5 and Upper limit + 0.5 Marks Frequency 0 - 9 2 10 - 19 5 20 - 29 2 30 - 39 1 Marks Frequency 0.5 – 9.5 2 9.5 – 19.5 5 19.5 – 29.5 2 29.5 – 39.5 1 Inclusive Data Exclusive Data
  19. 19. Need and purpose of Classification of Data • In the construction and standardization of various tests and measures. • In making proper use of the results of various tests and measures. (i) To know individual difference of our students. (ii) To compare the stability of our method and techniques (iii) To make comparison of system of evaluation (iv) To compare the function and work. (v) To make perdition regarding the future of students. (vi) To make selection (vii) For easy identification
  • KomalSaini59

    Aug. 16, 2021
  • kundagol

    Jun. 4, 2020
  • maitrihathi7

    Jun. 4, 2020

Collection and Classification of Data - Primary and secondary data , Classification of data, frequency array and frequency distribution

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