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Chapter 2 Chapter 2

Methods of Data Collection Methods of Data Collection

and Presentation and Presentation

 Two types of data: Primary and Secondary  Primary data: the investigator himself collects the data.  Secondary data: is not investigated by the investigator himself, but he obtains from someone else records.  Primary data collection methods: includes observation, personal interview, self administered questionnaire, mailed questionnaire etc.  Secondary data collection methods: obtained from published or unpublished documents: reports, journals, magazines, articles e t c.

2.1 Method of data collection 2.1 Method of data collection

 One way table: uses only one characteristics

• Two way tables: uses only two characteristics Sex Number of students Male 50 Female 30 Age Sex Male Female Below 19 5 8 19 – 24 45 20 Above 24 10 2

 Higher order tables: uses more than two characteristics 2.2.2 Frequency distributions

• (^) It is grouping of data into categories
• It is used to: - (^) organize data in a meaningful, intelligible way - (^) enable one to determine shape of the distribution - (^) how the observations cluster around a central value - (^) facilitate computational procedures - (^) enable one to draw charts and graphs - (^) enable one to make comparisons between data sets

Steps for constructing a frequency distribution

• (^) Range (R): Maximum value – Minimum value
• (^) Number of classes (K):
  • (^) Choose K to be between 5-
  • (^) Use Sturgess’ formula: K = 1 + 3.322 log (n) – round up the value of K
• (^) Class width (W): W = Range/K – round up the W value
• Tally the observations, count and assign frequencies to the classes

Example : The following data are on the number of minutes to travel from home to work for a group of automobile workers. 28 25 48 37 41 19 32 26 16 23 23 29 36 31 26 21 32 25 31 43 35 42 38 33 28 Construct a frequency distribution for this data. Solution:

• (^) Range = 49 – 16 = 32
• (^) K = 1 + 3.322 log(25) = 5.64 = 6
• (^) W = R/K = 32/6 = 5.33 = 6

Types of frequency distribution

• (^) Absolute frequency distribution: frequencies assigned are absolute numbers. The above example.
• (^) Relative frequency distribution: frequency assigned are relative frequencies
• Cumulative frequency distribution: a cumulative less than frequency distribution; and a cumulative more than frequency distribution

The relative frequency distribution is:

More than cumulative frequency distribution:

• 16-21 Time (in Minutes) Number of workers
• 22-27
• 28-33
• 34-39
• 40-45
• 46-51
  • Total
• 16-21 0. Time (in Minutes) Relative frequency
• 22-27 0.
• 28-33 0.
• 34-39 0.
• 40-45 0.
• 46-51 0.
  • Total
• Less than 15.5 Time (in Minutes) Cumulative frequency
• Less than 21.5
• Less than 27.5
• Less than 33.5
• Less than 39.5
• Less than 45.5
• Less than 51.5
• More than 15.5 Time (in Minutes) Cumulative frequency
• More than 21.5
• More than 27.5
• More than 33.5
• More than 39.5
• More than 45.5
• More than 51.5

Ungrouped frequency distributions Example : The following data is the number of cars in a sample of 30 government offices in SNNPR. 4 2 4 3 2 8 3 4 4 2 2 8 5 3 4 4 5 4 3 5 2 7 3 3 7 7 3 8 4 5 Construct ungrouped frequency distribution.

Categorical frequency distributions: Example: The following data are on the political party affiliations of sample of 40 students. D, R, and O stand for Democratic, Republican and Other, respectively. D D D D O R O R O R O R O D D R D D D R R O R D R R O R R R R R O O R R D R D D Construct ungrouped frequency distribution.

Number of students by political party affiliations Number of student Frequency Relative frequency Democratic 13 0. Republican 18 0. Other 9 0. Total 40 1

The frequency distribution is: Time (class boundaries) Class mark Number of workers 15.5-21.5 18.5^3 21.5-27.5 24.5^6 27.5-33.5 30.5^8 33.5-39.5 36.5^4 39.5-45.5 42.5^3 45.5-51.5 48.5^1

Figure 1: The time in minutes spent by automobile workers to travel from home to work.