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

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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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