DATA GATHERING. Define : Is a process of collecting data from sample, so as for testing & analyzing before reporting research findings.

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1 DATA GATHERING Define : Is a process of collecting data from sample, so as for testing & analyzing before reporting research findings.

2 2012 John Wiley & Sons Ltd. Measurement Measurement: the assignment of numbers or other symbols to characteristics (or attributes) of objects according to a pre-specified set of rules.

3 What is data? The Concise Oxford Dictionary known facts or things used as a basis for inference or reckoning. BBC English Dictionary data is information, usually in the form of facts or statistics that can be analysed. Ahmad 3

4 Data Classification Quantitative data observations that are numerical. Qualitative data observations that relate to categories (e.g., colour, sex, etc.) rather than numerical. Objective data observations based on observable facts. Subjective data involve personal feeling, attitudes and perceptions. (Note: Both objective and subjective data can be quantitatively or qualitatively measured). Longitudinal data collected over time. Ahmad 4

5 Data Classification Cross-sectional data collected at the same point in time, but over differing entities, such as districts or states. Primary data collected by the investigator directly at the source. Secondary data data that have been collected and recorded by another person or organisation, usually for different purposes that the issues at hand. Ahmad 5

6 Nominal Scale (Schloss & Smith, 1999; Burns, 2000) This scale is the most basic, primitive and least informative level of measurement. Observations are classified into categories with no necessary relationship existing between the categories. Reliability of measurement is judged solely by the accuracy with which categorization occurs. E.g., a reliable nominal scaling of hair colour reliably categorizes individuals as being brunettes, blondes, and redheads. The major analytic procedure for nominal data is chi square. Ahmad 6

7 Ordinal Scale (Schloss & Smith, 1999; Burns, 2000) This measurement implies the ability to put data into rank order. More often in educational research, ordinal scales consist of a collection of naturally ordered categories. To illustrate, social class may be classified into upper, middle and working; attitudes towards racial integration may be classified as very favourable, favourable, neutral, unfavourable or very unfavourable. The major analytic techniques for ordinal data are Wilcoxon, Mann-Whitney and rank order correlation. Ahmad 7

8 Ordinal Scale (Schloss & Smith, 1999; Burns, 2000) This measurement implies the ability to put data into rank order. More often in educational research, ordinal scales consist of a collection of naturally ordered categories. To illustrate, social class may be classified into upper, middle and working; attitudes towards racial integration may be classified as very favourable, favourable, neutral, unfavourable or very unfavourable. The major analytic techniques for ordinal data are Wilcoxon, Mann-Whitney and rank order correlation. Ahmad 8

9 Interval Scale (Schloss & Smith, 1999; Burns, 2000) Interval measurement, as is implied by the name, provides uniform differences between scale units. Interval scales have the property that there is a specific numerical distance between each pair of levels. Hence, we can compare values not only in terms of which is larger, but also in terms of how much larger or how much older. Example we can say that a sixty-year-old is of different age to a twenty-year-old individual (nominally, they are labelled differently according to age); that one is older (an ordinal comparison); and that one is forty years older (an interval Ahmad 9

10 Ratio Scale (Schloss & Smith, 1999; Burns, 2000) This is the highest and most complete form of measurement. Scores based on interval scale allow subtraction and addition, but they do not allow multiplication and division. Because of the completeness of information in a ratio scale, all statistical procedures can be used effectively. Ahmad 10

11 TEST (Burns, 2000) a. Attitude toward legalization of marujuana (in favour, neutral, oppose). b. Sex (male, female). c. Fatimah was born in 1968; Aiman in d. Sect affiliation (Shafi e, Maliki, Hambali,..) e. Political philosophy (liberal, moderate, conservative). f. The IQ of students. g. Highest degree obtained (bachelor, master, doctorate). Ahmad 11

12 TEST (Burns, 2000) h. Amin is the second most popular student in class. i. Average score in class test. j. Occupational status (blue collar, white collar). k. Numbering of houses along a road. l. Population size (number of people). m. Pass/fail split in a test. n. Annual income (in RM per year). o. Time taken to solve anagrams. p. Aptitude scores. [Answer] Ahmad 12

13 TOOLS FOR DATA COLLECTOTION Research instrument is the tool for data research collection Instrumentation is the process of making the research tool

14 TYPES OF INSTRUMENTS Research Developed: Questionnaire Interview Schedule Observation Form Opinionaire or Attitude Scale Document Analysis Form Researcher-made Achievement Test Standardized: Standardized Achievement Test Aptitude Test Ability Test Interest Inventory Projective Measures

15 CHARACTERISTICS OF INSTRUMENTS Standardized: Research-made: Standard administration procedures Standard scoring procedures Reliability and validity indices It doesn t have a standardized administration procedures or guide It probably does not have established reliability &

16 Survey TYPES OF DATA COLLECTION Observation Interview Standardized Instruments Documents

17 INSTRUMENTATION Feasibility The ability an instrument fits the need. It will work if it is feasible Validity The ability of the research instrument to fulfill the function for which it is being used Reliability The ability of the research instrument to yield highly consistent results for its usage (Measurement of Precision)

18 VALIDITY VS RELIABILITY The first consideration in social science research is always validity. Reliability is crucial prerequisite for validity, BUT it is only a means toward that end.

19 TYPES OF VALIDITY Content Validity Construct Validity Criterion-Related Validity 1. Predictive Validity 2. Concurrent Validity

20 CONTENT VALIDITY The degree to which the test actually measure the traits for which it was designed

21 CONSTRUCT VALIDITY The degree to which scores on a test can be accounted for of a sound theory

22 CRITERION-RELATED VALIDITY The coefficient of correlation between test scores and some measure of future performance or of known validity

23 PREDICTIVE VALIDITY The ability with an instrument s value in predicting future levels of performance in some specific endeavor

24 CONCURRENT VALIDITY The degree to which obtained scores on a particular instrument measure, when compared to other instrument of the same functions

25 TEST OF RELIABILITY Stability Equivalence Internal Consistency (Split-half) Internal Consistency (Kuder- Richardson)

26 RELIABILITY TESTING Reliability Co- Efficient Stability Equivalence Internal Consistency (Split-half) Internal Consistency (Kuder-Richardson) Information Provided A measure of consistency from one administration of an instrument to another To determine the likeness to two different forms of the same instrument To determine how consistent segments of the test with the Procedures Compare the results on two administration of the same instruments to the same individuals with any time lapse ensuing Compare two halves (odd and even times) of the test and make correction for the length with special formula Apply special formula to test results

27 MEASUREMENT Measurement is a process of assigning numerals according to rules. The numerals are assigned to events or object, such as responses or objects, such as responses to items or to certain observed behaviors

28 MEASUREMENT SCALE Parametric Scale: Ratio A measurement that has a zero point (absolute zero) Interval Measurement of equal unit between the numbers on the scale Non-Parametric Scale: Ordinal Measurement of identification & classification based upon quantitative qualities Nominal Assign numbers for the purpose of identification

29 LEVELS OF QUANTITATIVE DESCRIPTION LEVE L SCALE PROCESS DATA TREATMENT APPROPRIATE TESTS 4 Ratio Measured equal intervals True zero Ratio relationship 3 Interval Measured equal intervals No true zero 2 Ordinal Ranked in order 1 Nomina l Classified and counted Parametric Nonparametric T Test Analysis of Variance (ANOVA) Analysis of Covariance (ANCOVA) Factor Analysis Pearson s r Spearmen s rho (p) Mann-Whitney Wilcoxon Chi-square Median Sign

30 SUMMARY OF CHARACTERISTICS OF SCALE MEASUREMENTS SCALE CHARACTERISTICS OF SCALE EXAMPLE Ratio Interval Ordinal Numbers represent equal units absolute zero. Observations can be compared as ratios or percentages Equal difference between numbers represent equal difference in amounts of the attribute Numbers indicate rank order of observations Distances, age, time, weight Year (A.D) Percentile, norms, social status, class Nominal Numbers represent categories. Numbers do not reflect differences in magnitude. Numbers serve to distinguish groups. Sex, nationality, clinical diagnosis, college major

31 SAMPLING Random Sampling It is practiced for parametric statistics Non-Random Sampling It is practiced for non-parametric statistics

32 RANDOM SAMPLING Simple Random Stratified Random Cluster Random Two-Stage Cluster Random

33 POPULATIONS A B C F Y Z V E S D T I J H P G L R W K O M U X Q N A B C D E 25% F G H I J K L M N O 50% P Q R S T 25% AB QR ST U NO P EFG HI CD LM JK AB QR ST U NO P EFG HI CD LM JK Sample of Clusters CD STU LM Y D P L H Simple Random N B D 25% F M O J 50% P S 25% Stratified Random SAMPLES CD STU Cluster Random LM Sample of Individuals C,L,T Two-Stage Random

34 NON-RANDOM SAMPLING Convenience Purposive Systematic

35 A B C D E G H J K M N O P R S T U V W Z F POPULATIONS X L Y Q I X L Y Q I A B C D E F H I G J K L M N O P Q R S T U V W X Y Z A C D E B F G H I J K L M N O P Q R S T V U W X Y Z F B N V L G L B V Q Systematic Especially Qualified Purposive Easily Accessible Convenience