Data Analysis

Quantitative data: Reliability & Validity Reliability: the degree of consistency with which it measures the attribute it is supposed to measure Reliability: the degree of consistency with which it measures the attribute it is supposed to measure reliability measurement tools reliability measurement tools __ stability __ internal consistency __ internal consistency __ equivalence __ equivalence

Stability The extent to which the same results are obtained on repeated administration of the instrument The extent to which the same results are obtained on repeated administration of the instrument Obtained by test-retest reliability (same test for the same subjects in two occasions) Obtained by test-retest reliability (same test for the same subjects in two occasions) Reliability coefficient (the correlation between the two sets of testing; the test and the retest) Reliability coefficient (the correlation between the two sets of testing; the test and the retest)

Internal consistency All of the subparts of the instruments measure the same attribute All of the subparts of the instruments measure the same attribute Obtained by Split-half techniques (correlation between the two randomly split half of the instrument). Obtained by Split-half techniques (correlation between the two randomly split half of the instrument). Mostly reported by the values of cronbach’s alpha, and Kuder-Richardson formula 20 (KR20) Mostly reported by the values of cronbach’s alpha, and Kuder-Richardson formula 20 (KR20)

Equivalence Used when: Used when: 1. Different researchers used the same instrument to measure the same phenomenon 2. Two instruments are used at the same time Obtained by the methods of Interrater reliability (two well-trained observers to the same phenomenon simultaneously) Obtained by the methods of Interrater reliability (two well-trained observers to the same phenomenon simultaneously) Either by correlation or agreement formula Either by correlation or agreement formula

Validity The instrument measures what is suppose to measure The instrument measures what is suppose to measure Content validity Content validity Criterion-related validity Criterion-related validity Construct validity Construct validity Interpretation validity Interpretation validity

Qualitative data Credibility: confidence in the truth of data Credibility: confidence in the truth of data Transferability: Generalizability of the data Transferability: Generalizability of the data Dependability: stability of data over time and conditions Dependability: stability of data over time and conditions Confirmability: objectivity or neutrality of the data Confirmability: objectivity or neutrality of the data

Descriptive Statistics Levels of measurements Levels of measurements 1. Nominal 2. Ordinal 3. Interval 4. ratio

Shapes of distribution Shapes of distribution 1. Normal distribution 2. Skewed distribution (positive and negative) 3. unimodal __ bimodal __ multimodal

Central tendency : Central tendency :  Mode:  Median:  Mean: 5.4  Standard deviation: the average deviation of the data from its mean  Variance: SD 2  Range, inter-quartile range

Data Analysis-2

Data Interpretation Consideration: Consideration: 1. Accuracy - critical view of the data - investigating evidence of the results - investigating evidence of the results - consider other studies’ results - consider other studies’ results - peripheral data analysis - peripheral data analysis - conduct power analysis: type I & type II - conduct power analysis: type I & type II CorrectType-II Type -I Correct True False

alpha : the level of significance used for establishing type-I error alpha : the level of significance used for establishing type-I error β : the probability of type-II error β : the probability of type-II error 1 – β : is the probability of obtaining significance results ( power ) 1 – β : is the probability of obtaining significance results ( power ) Effect size: how much we can say that the intervention made a significance difference Effect size: how much we can say that the intervention made a significance difference

2. Meaning of the results - translation of the results and make it understandable - translation of the results and make it understandable 3. Importance: - translation of the significant findings into practical findings - translation of the significant findings into practical findings 4. Generalizability: - how can we make the findings useful for all the population - how can we make the findings useful for all the population 5. Implication: - what have we learned related to what has been used during study - what have we learned related to what has been used during study