Research Methods Midterm #1 Flashcards
Tenacity
- Superstition/habit
- Info may not be accurate/No method for correcting
Authority
- Find answers by seeking out an authority on the subject
- Quickest/easiest way to obtain answers
- (doctors, parents, lawyers)
- not all “experts” are experts, personal opinion/biases
Rationalism
- Logical reasoning
- Begin with set of known facts/assumptions
- Even if logic is sound, the conclusion may not be true
Empiricism
- Direct observation or personal experience
- Too much confidence in observations
- Perceptions can drastically alter by prior knowledge, expectations, feelings, or beliefs
Inductive vs. deductive logic
- Inductive: small set of specific observations used for forming a general statement about a larger set of possible events.
- Deductive: General statement or set of statements as the basis for reaching a conclusion about specific examples
Testable hypothesis
- possible to observe and measure all variables involved
Refutable hypothesis
- contrary results must be possible
- in other words, the hypothesis must be falsifiable
Operational definitions
Limitations:
- they may leave out important components of a construct
- they may include components that are not part of the construct being measured
Using operational definitions:
- to determine how a variable should be measured, consult previous research involving the same variable
Intuition
- “gut feeling”
- many ethical decisions or moral questions are resolved by the method of intuition
Steps in the research process
- Observe
- General Hypothesis
- Research Hypothesis
- Evaluate
- Support, refute, or refine
Applied research
Research studies that are intended to answer practical questions or solve practical problems.
Basic research
Research studies that are intended to answer theoretical questions or gather knowledge simply for the sake of new knowledge.
Informed consent
The ethical principle requiring the investigator to provide all available information about a study so that a participant can make a rational, informed decision regarding whether to participate in the study.
Inter-rater reliabilty
The degree of agreement between two observers who simultaneously record measurements of a behaviour.
Debriefing
A post-experimental explanation of the purpose of the study. A debriefing is given after a participant completes a study, especially if deception was used.
Fraud
The explicit efforts of a researcher to falsify and misrepresent data. Fraud is unethical.
Plagiarism
Presenting someone else’s ideas or words as one’s own. Plagiarism is unethical.
Face validity
An unscientific form of validity that concerns whether a measure superficially appears to measure what it claims to measure.
Concurrent validity
The type of validity demonstrated when scores obtained from a new measure are directly related to scores obtained from more established measure of the same variable.
Interval
- Scale must have equally-spaced units (distance along intervals equal)
- Zero is just a point on the scale (not absence of the construct)
- E.g., temperature, clock hour, psychological sclaes
- 1(strongly disagree) - 7(strongly agree)
Divergent validity
- Two different methods to measure two different constructs.
- Convergent validity must be shown for each of the two constructs.
- There should be little to no relationship between the scores obtained for the two different constructs when they are measured by the same method.
Convergent validity
- Strong relationship between the scores obtained from two different methods of measuring the same construct.
Contructs
Hypothetical attributes or mechanisms that help explain and predict behaviour in a theory.
Operational definition
- A procedure for indirectly measuring and defining a variable that cannot be observed or measured directly.
- Specifies a measurement procedure (a set of operations) for measuring an external, observable behaviour and uses the resulting measurements as a definition and a measurement of the hypothetical construct.
Alpha
In a hypothesis test, the criterion for statistical significance that defines the maximum probability that the research result was obtained simply by chance.
- Also known as level of significance
Ratio
- The scale must have a true 0 point and ratios must be calculable
- E.g., height, weight, reaction time
Mean
A measure of central tendency obtained by adding the individual scores, then dividing the sum of the number of scores. The mean is the arithmetic average.
Median
List the values of the data set in numerical order and identify which value appears in the middle of the list. “Middle”
Mode
Identify which value in the data set occurs most often.
What is a normal curve? How do we use normal curves?
- Many variables we are interested in have a “bell” distribution (shape)
- E.g., IQ, weight, the number of hours spent studying”
What is a z-score? How do we use them? How do we calculate z-scores?
- A z-score is the number of standard deviations a score is from the mean
Uses: 1. Assessing the relative position of a score in a distribution. 2. Assessing the probability of attaining a score or mean at or below, or higher, than that score or mean in the population
What is a hypothesis test? What is its purpose?
A process of ruling out chance as a possible explanation for findings.
Sampling error
The naturally occurring difference between a sample statistic and the corresponding population parameter.
Standard error
A measure of variability that describes the average distance between a sample statistic and the corresponding population parameter
Null hypothesis vs. Alternative hypothesis
- There is no effect, no change, no relationship
- Any differences between the sample and the population occurred due to chance
vs. - The hypothesis of our predicted effect (Corresponds to Research Hypothesis)
Population vs. sample
Everyone you are interested in vs. who you are actually using in your study
Significant result
A result that is extremely unlikely to have occurred simply by chance
Type I error vs. Type II error
Type I error - Reject the null hypothesis/ null hypothesis is true
Type II error - Fail to reject null hypothesis/null hypothesis is false.
Standardized normal curve
This is the “bell-shaped” curve of the Standard Normal Distribution. It is a Normal Distribution with mean 0 and standard deviation 1. It shows you the percent of population: between 0 and Z (option “0 to Z”)
