PSYC 1010 Lecture Notes - Lecture 4: Frequency Distribution, Null Hypothesis

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15 Nov 2017
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Basic Statistics: Using Math to Describe & Analyze Data
1) Descriptive- Using Numbers to describe what’s going on; Organize lots of data
into meaningful patterns & summaries; Reveal what the data looks like
a. Frequency Distribution- how often a score appears in a set of scores
A) Rank order of scores & Group ranking
b. Graphs- Visual Representation of frequency distribution (Be careful of
scale differences)
c. Central Tendency- Instead of working with all the scores, get an index of
the most typical scores; get measures of how variable scores are, as
compared to the most typical
A) Mean; Median; Mode
B) Range- The difference between the highest and the lowest
C) Standard Deviation (sd)- Extent to which scores fall away from the
mean
1. Small sd = Scores are pretty similar
2. High sd = Scores more spread out
d. Correlation Coefficients (r) (-1 to +1)
2) Inferential- Used to test hypotheses and differences (crux of research); Allow
inferences to be made about applicability of results to larger populations…
a. Null Hypothesis- there’s no difference between the 2 groups being tested
against each other.
A) Statistical Significance- Are the scores generally about the same?
(Fail to reject = right) Are the scores clearly different? (Reject =
wrong)
3) Statistical Significance & Power
a. Power- Degree of confidence in conclusion; p < 0.05 = probably less than
5% chance the findings you are seeing are just due to chance or
coincidence (95% chance the findings show something real)
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