Foundation Research Methods
- Created by: saraaazamann
- Created on: 27-12-16 14:20
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- Foundation Research Methods
- Central modes of tendency (tells us where the cluster is)
- Mean = (sum of all scores)/number of scores
- The mean describes the average of a set of data
- Mode = the most common value in your data set.
- Median = the middle score of the ranked data
- Mean = (sum of all scores)/number of scores
- Normal Distribution
- Most of the numbers that we deal with are normally distributed (symmetrical bell shaped graph)
- Standard Deviation
- SD = the square root of the mean deviation of all the data from the mean is the standard deviation. Tells us about how the data is distributed
- SD means that the values in a statistical data set are close to the mean of the data set. On average a large SD means that the values in the data are set farther away from the mean, on average.
- Histograms
- The X-axis covers the full range of possible scores. The Y-axis shows how frequent particular scores are.
- Skewed distribution
- Left/negative skew = your test is too easy. Right/positiveskew = your test is too hard
- Narrow distribution = not enough variation. Wide Distribution = too much variation
- Research Designs
- Experimental = the process of planning a study to meet specified objectives. Use only IV's
- Quasi-experimental = employed when the researcher is interested in IV's that cannot be randomly assigned.
- Correlational = looking for relationships between DV's
- Types of data (i.e. numeric/categorical
- Numerical = reaction time, IQ, Likert scale responses
- Categorical = eye colour, political affliction
- Experimental Designs
- Between-subjects = if each person belongs to only one level of the variable.
- Within subjects variable (also RMD) = if each person belongs to every level of the variable.
- Correlations (positive/negative/no correlation
- Interested in the relationships between DV's. A change in one variable is usually accompanied by a change in another variable. (don't investigate cause and effect)
- Avoiding Order Effects
- Counter-balancing = the sample would split into two groups. Group 1 does A then B, group 2 does B then A. This is to eliminate order effects.
- Variables
- IV = these change according to the researchers wishes
- SV = these change according to characteristic of the ppts
- DV = these change according to how the ppts responds to the IV
- Significance levels
- If the p is less than 0.05 the data is shown to be significant.
- KS test
- Generates a normal distribution with the same mean and SD as your data and compares this frequent distribution to that from your data.
- Central modes of tendency (tells us where the cluster is)
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