Lecture 4: Lab Methods Flashcards
1
Q
Deductive reasoning
A
- Top down process of collecting and analyzing data to support or refute hypothesis
2
Q
Inductive reasoning
A
- Bottom up process of gathering data, looking for patterns in that data and developing a hypothesis based on those limited observations
3
Q
Quantitative vs qualitative research
A
- Quantitative: uses measurable data in a series of steps
1a. Question: intro
1b. Hypothesis: intro
1c. Study design: methods
1d. Data collection: result
1e. Data analysis: result
1f. Conclusion: discussion - Qualitative: uses verbal data
4
Q
Types of variables
A
- Independent: one that researchers manipulate and control (x axis on graph)
- Dependant: depends on independent/whats being measured (y axis)
5
Q
Types of measurement scales
A
- Nominal: non order categories
- Ordinal: ordered categories (categories by rank order)
- Interval: intervals between values are meaningful
- Ratio: has an absolute 0 and ratios between values are meaningful
6
Q
Types of errors
A
- Random error: decreases precision (reliability)
1a. Precision: all shots in one spot - Systematic error: decreases accuracy (validity)
2a. Accuracy: shots where they need to be
7
Q
Research biases
A
- Sampling (Selection) bias: non representative sample
- Observer bias: when observer intentionally or unintentionally records a distorted measurement
- Instrument bias: systemic malfunctioning of a instrument
- Subject (participant) bias: when subject intentionally or unintentionally reports a distorted measurement
8
Q
Experimental study designs
A
- Scientists manipulate 1+ variables in order to observe outcome
- Needs control groups: treated the same as experimental group w/o the treatment
2a. Positive controls: when effect is expected bc scientists manipulate them in a way that is already known to produce the effect
2b. Negative control: no effect is expected - Sample needs to have random assignment (randomly in control or experimental groups) & the best experiments are double blind (researcher and subject dont know which groups either are in)
- Quasi experimental study: when random assignment is not possible which makes determining causality more difficult
9
Q
Observational studies
A
- When scientists observe variables without manipulating them
10
Q
Types of studies in reference to data collection
A
- Cross sectional studies: investigate many participants in present time/one day
- Longitudinal: follow same participants over a long time
2a. Cohort studies: prospective (looking forward) or retrospective (looking back)
2b. Case control studies: always retrospective
11
Q
What are the negatives of prospective and retrospective studies
A
- Prospective: expensive and risk losing participants over time
- Retrospective: recall bias
12
Q
Values in a data set can be:
A
- Categorical/qualitative data
1a. Nominal
1b. Ordinal - Numerical/quantitative data
2a. Interval
2b. Ratio
13
Q
Descriptive statistics: central tendency
A
- Mean/average: sensitive to outliers
- Median: middle value
- Mode: most common variable
14
Q
Descriptive statistics: measures of dispersion
A
- Range: large range=large dispersion
- Interquartile range: dispersion at middle half data
- Standard deviation: how far values are from mean (if large=widely dispersed data)
15
Q
Inferential statistics
A
- To determine whether data collected support or refute hypothesis of experiment: draws inferences about data (data is described by differential statistics)
- Correlation: varies from -1 to 1 (best correlation at both values)
2a. -1: negative correlation
2b. 1: positive correlation) - Hypothesis testing:
3a. Null hypothesis: no sig difference … goal is to reject this (occurs if research is statistically different)
