TYPES OF RESEARCH

Qualitative Research

• understanding human behavior from the informant’s  perspective

• data are collected through participant observation and interviews 

• is interpretative and does a naturalistic approach to its subject matter (Denzen and Lincoln, 1994)

• aims to understand the social reality of individuals, groups, and cultures 

• “how” and “why” a particular phenomenon happens

Quantitative Research

• discovering facts about social phenomena

• assumes a fixed and measurable reality

• data are collected through numerical comparisons 

• put into categories, in rank order, or measured in units of measurement

• aims to establish general laws of behavior and phenomenon across different settings/context

• research is used to test a theory and ultimately support it or reject it

TWO MAIN METHODS OF RESEARCH

1. Deduction – general theory to particular data

2. Induction – particular data to a general theory

THEORY AND HYPOTHESIS

Theory - explanation or set of principles that are well substantiated by repeated testing and explains a broad phenomenon.

e.g.  People   diagnosed   with   depression  prefer to sleep more and stay at home than those who  are not depressed

Hypothesis - a proposed explanation for a fairly narrow phenomenon or set of observations

e.g. People diagnosed with depression prefer to sleep and stay at home often because they are easily drained of energy

VARIABLES IN RESEARCH

1. Independent Variable - the cause of some effect manipulated by the experimenter

2. Dependent Variable - affected by changes in an independent variable

RANDOMIZATION IN REPEATED-MEASURES DESIGN

1. Practice effects - participants perform differently in the second condition because of familiarity with the experimental situation 

2. Boredom effects - participants may perform differently in the second condition because they are tired or bored from having completed the first condition

Counterbalancing – is usually thought of as a method for controlling order effects in a repeated measures design

ANALYZING DATA

CENTRAL TENDENCY

• the center of the distribution of scores 

a. The Mode – the score that occurs most frequently in the data set (bimodal; multimodal)  

b. The Median - the middle score 

c. The Mean - the sum of all scores divided by the number of scores

EXAMPLE: 

13, 18, 13, 14, 13, 16, 14, 21, 13

find the mean: 

(13 + 18 + 13 + 14 + 13 + 16 + 14 + 21 + 13) ÷ 9 = 15

find the median: 

= 13, 13, 13, 13, 14, 14, 16, 18, 21 

=  (9 + 1) ÷ 2 = 10 ÷ 2 = 5th number

= 13, 13, 13, 13, 14, 14, 16, 18, 2

find the mode:

= most repeated number: 13

DISPERSION

• is the extent to which a distribution is stretched or squeezed 

a) Quartiles - three values that split the sorted data into four equal parts

b) Lower Quartile - the median of the lower half of the data

c) Upper Quartile - the median of the upper half of the data

d) Interquartile - difference between the upper and lower quartile

e.g. 1) 5, 7, 4, 4, 6, 2, 8     

= 2, 4, 4, 5, 6, 7, 8     

Q1 (lower quartile) = 4     

Q2 (interquartile) = 5     

Q3 (upper quartile) = 7

e. Mean Absolute Deviation (MAD) - is the average distance between each data value and the mean; helps us get a sense of how "spread out" the values in a data set are

e.g. 1)  the Mean Deviation of 3, 6, 6, 7, 8, 11, 15, 16

Mean