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Published byRobert Casey Modified over 9 years ago
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Two basic types Descriptive Describes the nature and properties of the data Helps to organize and summarize information Inferential Used in testing hypothesis (e.g., differences between groups, relationships between variables) Statistics
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Describing Individual Differences Measures of Central Tendency Measures of Variability Distribution of the data
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Measures of Central Tendency Mean average score of all observations in distribution Median midpoint of all scores in distribution Mode most frequently occurring score in distribution Descriptive Statistics
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Measures of Variability Range subtract the lowest from the highest score and add 1 Standard Deviation measure of the “spread” of the scores around the mean Descriptive Statistics
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∑(x i – x) 2 n-1 √ Calculating the standard deviation (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
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Frequency Plots ScoresTalliesFrequency 6I1 5III3 4IIII4 3IIIII5 2III3 1II2 0 2 Frequency Distribution
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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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Properties of a normal distribution 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%) Normal Distributions
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The extent to which one variable can be understood on the basis of another Two 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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Negative Correlation r = -.95 LowHigh Low High
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Data Set 3 Example Scatter Plot
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