Department

Communication StudiesCourse Code

CS235Professor

Naveen JoshiLecture

5This

**preview**shows half of the first page. to view the full**3 pages of the document.**Formulating a Hypothesis

Seale β Page 344 β 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 β analysis is of only one variable)

- We usually have more than one variable

- Bivariate analysis β two variables

- Multivariate analysis β more than two variables

Example β 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 β gender and laptop use

- Indicator β 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

- Donβt 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 β 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 β most students do well on exam, a few tank the exam β this brings the average down,

but it is only a few students, so the results are negatively skewed for the class

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