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Published byGertrude Thomas Modified over 9 years ago
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Describing Behavior Chapter 4
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Data Analysis Two basic types Descriptive Summarizes and describes the nature and properties of the data Inferential What is the likelihood the results in the sample actually occur in the population (e.g., differences between groups, relationships between variables)
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Describing Individual Differences Measures of Central Tendency Measures of Variability Distribution of the data
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Mean average score of all observations in distribution Median midpoint of all scores in distribution Mode most frequently occurring score in distribution Measures of Central Tendency
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Range subtract the lowest from the highest score Standard Deviation measure of the “spread” of the scores around the mean – Variance square of the standard deviation Measures of Variability
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∑(x i – x) 2 n-1 √ (1 – 3) 2 + (2 – 3) 2 + (3 – 3) 2 + (4 – 3) 2 + (5 – 3) 2 5 - 1 √ (-2) 2 +(-1) 2 +(0) 2 + (1) 2 + (2) 2 5 - 1 √ 4 + 1 + 0 + 1 + 4 4 √ 1 2 3 4 5 15 3 Sum Mean Data 10 4 √ 2.5 √ 1.58 Calculating the standard deviation
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Data Distributions
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Descriptive Statistics Distribution of the data Shapes of distribution curves Bell (normal distribution) The bell curve has desirable statistical properties A number of inferential statistics “assume” data is normally distributed Skewed Curves Negative Skew - tail of the curve is to the left Positive Skew - tail of the curve is to the right
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Measures of central tendency are the same mean = median = mode We know percentage of scores that fall within 1 standard deviation (68%) 2 standard deviations (95%) 3 standard deviations (99%) Properties of a Normal Distribution
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The extent to which one variable can be understood on the basis of another Properties of correlation coefficient direction (positive or negative) magnitude (strength of the relationship) Correlation
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r =.95 Positive Correlation
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r =.00 No Correlation
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r = -.95 LowHigh Low High Negative Correlation
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Correlation: A Review
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Distribution for Example M = 3.00 SD = 1.10
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