GLHLTH 371 Lecture Notes - Lecture 7: Standard Score, Central Tendency, Statistical Parameter

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9 May 2016
Analyzing Data Using Statistics
****need to know how to calculate all measures of central tendency and measures of variability
I. Descriptive Statistics
a. Summarize raw data
b. Frequency distribution: table that shows number of scores that fall within each category
c. Histogram: graphical representation of a frequency distribution
c.i. Used when scores are on an interval or ratio scale (continuous variables)
II. Descriptive Statistics for Continuous Variables
a. Measures of central tendency: in a normal distribution, all three are the same
a.i. Mean
a.ii. Median
a.iii. Mode
b. Measures of variability
b.i. Range: difference between smallest and largest score
b.ii. Variance: index of average variability
b.iii. Standard deviation (SD): index of variability in scores in original scores; can be
used to describe variability in meaningful terms; whereas variance isn’t in units
of your measure
b.iv. Z-score: a standard score, used to describe how far a participant’s score varies
from the mean in terms of SDs; z = (score-mean)/standard deviation
b.iv.1. **1 SD from mean (both directions)= 68%; 2 SDs: 95%; 3 SDs:
99.7% (know these numbers)
III. Inferential Statistics
a. Used to draw inferences about a population based on easurement from a sample
b. These are assumptions; we hope that these are accurate reflections of the population
(parameter); sample is a statistic
c. Population parameter
c.i. Quantitative summary of variable in the population
c.ii. Has a fixed value that does not vary
d. Sample statistic
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