Research Methods II.2
Home > Preview
The flashcards below were created by user
on FreezingBlue Flashcards.
Steps of Hypothesis Testing 1
research hypothesis - an empirically testable statement derived from theory. It is stated in terms of the population. It holds for the whole population, but we only have a sample.
Steps of Hypothesis Testing 2
null hypothesis - the opposite of the research hypothesis given as a fixed value.
Steps of Hypothesis Testing 3
Assume the null - to derive a sampling distribution. A mathematical probability distribution, we do not find it empirically
Steps of Hypothesis Testing 4
Determine the critical region - 5% or less
Steps of Hypothesis Testing 5
Calculate a test (sample) statistic
Steps of Hypothesis Testing 8
Make a decision - infer about research hypothesis
Steps of Hypothesis Testing 6
One tailed test: a statistical test where extreme results leading to rejection of the null hypothesis can be located at only one tail
Two Tailed Test: A statistical test where extreme results leading to rejection of null hypothesis will be located at both left and right tails
Steps of Hypothesis Testing 7
- Type 1 Error: Rejecting a True Null
- Type 2 Error: Affirming a False Null
What is a significance level?
Probability of a type 1 error
What are confidence levels?
The probability that the value of a parameter falls within a specified range of values. Constructed with Z distributions.
Explain what happens to a sampling distribution as sample size increases and why this occurs.
As sample size increases sampling distribution decreases and vice versa. This occurs because there is a smaller chance of an error.
What is a PRE?
How much better can we estimate Y, the dependent variable, using X, than if we estimate Y by itself
Five Measures of Bivariate Association (description, associated levels, problems)
3. Kendall's Tau
4. "r squared"
5. "r" not PRE
For nonspurious bivariate relationships.
Usually involves the introduction of other variables to determine the links between the independent and dependent variables, or specification of the conditions under which association takes place.
What can happen when you control for a third variable in a bivariate relationship? (3 Things)
1. Nothing (Z has no effect)
2. The correlation between X and Y reduces drastically. This may mean: spuriousness OR Z is an intervening variable
3. The relationship between X and Y changes but does not disappear: then Z is a conditional variable
What is Lambda?
(PRE) measure of association for two nominal variables or 1 nominal+1 ordinal variable. Problem: it equals zero when the modes all fall in one value of the dependent variable. Then you use a percentage comparison instead.
What is Gamma?
(PRE) measure of association for two ordinal variables. Can be negative, varies from -1.00 to +1.00; Problem: it inflates the correlation because it doesn't include “ties"
A measure of association for two ordinal variables. It corrects the gamma problem by including “ties.” NOT a PRE
What is "r squared" for?
It is a PRE, scale of 0 to 1, for intervals and ratios
What is "r" (non-PRE)?
Uses a scale of -1 to 1, both assume linear relationship, for intervals and ratios
What factors are appropriate to consider in control and elaboration? (5)
Discuss the major issues in questionnaire construction (5 Things)
What do you want to know? What do you expect respondents to know?
Question Content: Fact or Opinion, wording, provide middle alternatives
Question Type: Closed vs Open-ended
Response Format for Closed-ended
8 Considerations for evaluating a poll
1. Topic: is it something people know about?
2. Screen for non-attitudes – Did the organization give respondents middle alternatives?
3. Question wording: Did the organization give you the question wordings?
4. Question Order: Questions can be placed to lead respondents in certain ways
5. Sample definition: Probability sample? From what population?
6. Sub-sample sizes and error margins. What happens if certain demographics are pulled out? (error margin increases)
7. Who sponsored the poll?
8. What's the spin?
Interviewer-administered Surveys - Advantages (3)
Higher response rate
Can probe and clarify
Interviewer-administered Surveys - Disadvantages (3)
Possible interviewer bias
Self-administered Surveys - Advantages (4)
No interviewer bias
Self-Administered Surveys - Disadvantages (4)
Lower Response Rate
Requires simple questions and answers
Nobody there to clarify/probe
Takes time (opportunities for outside phenomena to interfere)
Secondary Analysis - Advantages (3)
May be the only source
You can replicate/triangulate someone else's research with your own
Secondary Analysis - Disadvantages (3)
May only approximate the data you want
May have hidden biases
Sometimes access is a problem
Focus Groups - Advantages (5)
Less prep time
Don’t need to construct a survey
With a survey you only get what you ask for
In depth information
Focus Groups - Disadvantages (3)
No external validity
Results open to interpretation
Demand characteristics: People know they are being recorded/films. So people may not want to state their true feelings
Issues of Ethics in Conducting Research (5)
Settings and procedures
Informed consent: full disclosure, individual comprehension, competence
Privacy: public/private settings
8 Steps of Hypothesis Testing
Research Hypothesis: an empirically testable statement derived from theory. It is stated in terms of the population. It holds for the whole population, but we only have a sample.
Null Hypothesis: the opposite of the research hypothesis given as a fixed value.
Assume the Null: to derive a sampling distribution. A mathematical probability distribution, we do not find it empirically
Determine the Critical Region: 5% or less
Calculate a test (sample) statistic
One and Two Tailed Tests: One tailed test: a statistical test where extreme results leading to rejection of the null hypothesis can be located at only one tail. Two Tailed Test: A statistical test where extreme results leading to rejection of null hypothesis will be located at both left and right tails
2 Error Types: Type I error is to rejecting a true null. Type II is failing to reject a false null.
Make a decision - infer about your research hypothesis.
What would you like to do?
Home > Flashcards > Print Preview