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Lecture 5

# lecture 5 qualitative methods

Department
Communication Studies
Course Code
CS235
Professor
Naveen Joshi
Lecture
5

This preview shows half of the first page. to view the full 3 pages of the document. Formulating a Hypothesis
Seale Page 344 347
- Hypothesis is made up of a
o Dependent variable
o Independent variable
o Intervening variable
Variables
- Are the product of the concept-indicator link (Operationalization)
- Values of an indicator vary according to case
- Univariate analysis (ie. gender analysis is of only one variable)
- We usually have more than one variable
- Bivariate analysis two variables
- Multivariate analysis more than two variables
Example Gender and Laptop Use
- Proper use of the laptop during class time is determined by the gender of the user
- You need to make a choice and then make a statement as to which variable is independent and
which is dependent
- Our statement says that gender is the independent variable and the laptop use is the dependent
variable
- Concept gender and laptop use
- Indicator male and female, and what sites are you on during class, how often are you on the
class website, how much use is course content?
- Intervening variable could include the colour of the laptop
- You may find that there is a positive relationship between gender and laptop use, ie. females
use their laptops more appropriately than males
- The higher the female population, the more appropriate the laptop use
- Don’t worry about the findings, just know the dependent, independent, and intervening
variables making up the hypothesis
Measures of Central Tendency
MEAN = Average of the distribution of the variable
MEDIAN = number positioned in the middle of the distribution
MODE = most frequent occurring value in a distribution
Standard deviation = how far the data deviates from the mean
Normal distribution = mean, median, and mode are all the same
Shape of Distributions
- Distributions can be either symmetrical or skewed, depending on whether there are more
frequencies at one end of the distribution than the other
- Negatively skewed distributions distributions which have few extremely low values
(median>mean) - average is less than the number positioned in the middle
- Mass of the distribution is to the right, mean is lower than the median, which is lower than the
mode
- Example most students do well on exam, a few tank the exam this brings the average down,
but it is only a few students, so the results are negatively skewed for the class