DECK 2: (P2) IV & DV Flashcards
Determine the IV & DV of this example:
Dr Spock wanted to determine whether eating crusts does make your hair curly.
IV: Whether Individuals eat crusts or not
DV: Whether hair is curly or not
Interpret an Extraneous & Confounding Variable.
An extraneous variable are variables that may have an unforeseen effect on the dependent variable and effect the results in an unwanted way. A confounding variable is any variable that does have an unwanted effect on the DV in an experiment, making it impossible to determine which variable caused a change in the DV.
Give an example of a EV and a CV.
Examples of the EV/CV:
- Time of the day
- Weather conditions
- individual participants differences in characteristics
- Motivation/mood
Compare and Contrast between a Extraneous Variable and and Confounding Variable.
A Extraneous Variable is a variable that may have an unforeseen effect on the dependant variable in an unwanted way whereas a confounding variable is any variable that does have an unwanted effect on the DV. The confounding variable makes it impossible to discover which variables caused a change in the DV.
Which is NOT an example of a EV/CV?
a. Time of the Day
b. how much sleep the participant received
c. Weather Conditions
d. Motivation or Mood
b. how much seep the participant received
What is Population?
The whole large group that is of interest to the researcher.
What is Sample?
The smaller subgroup that has been selected to participate in the research.
TRUE OR FALSE:
A sample is majority of the group and each participant has volunteered to participate.
FALSE: A sample is the smaller subgroup that has been selected to participate in the research.
Describe a diagram of Sample & Population.
A group with selected people being taken out of the group.
Must sample be representative of the population? Why?
Yes, sample must be representative of the population because the purpose of research is to learn about the population. Conclusions can be drawn from this and can be generalised back to the population. Conclusions are pointless unless this occurs.
How many sampling procedures are there and what are they?
There are 3 types of sampling procedures. They are:
- Random
- Stratified Random
- Convenience
TRUE OR FALSE: The sampling procedure, ‘random’, includes picking out whoever is available at the time.
FALSE: The random sampling procedure means every member of the population has an equal chance of selection. An example:
- List of population
- Random number generator
Explain the strengths and weaknesses of the ‘Random’ sampling procedure.
The strength is that it gives a representative sample - participant variables spread in same proportion as in population.
The weakness is that it is difficult to achieve. The larger the population, the harder it is to list all individuals.
