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StatisticsSlidesAndNarration

# StatisticsSlidesAndNarration - Statistics Slides from the...

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Page 1 Statistics – Slides from the Podcast (The text of the podcast narration begins on page 4 below) Descriptive Statistics Measurements of subject responses on a variable are summarized using descriptive statistics: A histogram plots score ranges along the horizontal axis and score frequencies along the vertical axis. Basic Descriptive Measures The central tendency is a statistic that indicates what the typical score is like in the distribution of scores. Mean : Statistical average of all scores. Median : The fiftieth percentile (half of the scores are above this score, half are below). Mode : The most frequent score. Basic Descriptive Measures (Cont.) Relative standing: Percentile rank . Variability is how dispersed the scores are relative to the average score. Standard deviation : The average of how much the participant scores deviate from the mean. The Normal Distribution Examples: Height, Aggressiveness, IQ Test Scores, Anxiety Features of the Normal Distribution 0 5 10 15 20 25 30 '60 '59 '58 '57 '56 '55 '54 '53 '52 '51 '50 '49 '48 '47 '46 '45 '44 '43 '42 '41 '40 '39 '38 '37 '36 '35 '34 '33 '32 '31 '30 '29 '28 '27 '26 '25 '24 '23 34.1% 34.1% 13.6% 13.6% 2.1% 0.1% 0.1% -3 Standard Deviations -2 Standard Deviations -1 Standard Deviation +1 Standard Deviation +3 Standard Deviations +2 Standard Deviations Mean 2.1%

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Page 2 Approximating the Normal Curve Very often a distribution can deviate from a perfect normal curve but yet be close enough that all the statistics that assume a normal curve still work well. For example, exam scores often approximate a normal curve. Inferential Statistics When differences between conditions are found, were they due to chance or to real differences among the different conditions? Mathematical tests of statistical significance answer this question. p-value : Probability the result was due to chance. By convention in psychology, when p = .05 or less, the result is taken to be significant. Variance and Significance Same mean, difference variance Be Careful with Statistical Inferences When a difference is significant, you can conclude that it is real. However, the fact that a difference is statistically significant does NOT mean that it is large or important. The difference may or may not be large or important. Whether a significant difference is large or important will depend on other considerations. Inference Example 1: Suppose there was a product called the Genius Calculus Study Program that was priced at \$5,000. We decide to do an experiment to see if the program works. We randomly assign one group of students to study for 10 hours a week with the Genius Calculus Study Program, and another group of students to study 10 hours a week in their usual way. Inference Example 1 Continued
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StatisticsSlidesAndNarration - Statistics Slides from the...

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