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Reporting Descriptive Data

by: Amy Turk

Reporting Descriptive Data PSYC-31574-003

Marketplace > Kent State University > Psychlogy > PSYC-31574-003 > Reporting Descriptive Data
Amy Turk

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About this Document

Frequency distributions and variability. Notes for Exam 2.
Research Methods In Psychology
Dr. Tanjeem Azad
Class Notes
Psychology, Survey, Sampling, Probability, Frequency Distributions
25 ?




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This 2 page Class Notes was uploaded by Amy Turk on Monday April 4, 2016. The Class Notes belongs to PSYC-31574-003 at Kent State University taught by Dr. Tanjeem Azad in Spring 2016. Since its upload, it has received 27 views. For similar materials see Research Methods In Psychology in Psychlogy at Kent State University.


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Date Created: 04/04/16
REPORTING DESCRIPTIVE DATA ● Should be accurate, concise, and understandable Frequency Distributions ● Summarizes raw data by showing the number of scores that fall in each of several categories ● Simple frequency: ​number of participants who obtained each score ● Raw scores: a​rrange raw scores from lowest to highest ○ Count the frequency of each score ● Simple frequency distribution:​um of frequency of scores should total sample size in study ○ Histogram: frequency column on y-axis and scores on x-axis ■ Arrange from low to high ● Grouped frequency:​ subsets of scores ○ Ensure equal intervals ○ Same histogram format ● Mean: average ● Median: middle number ● Mode: most frequent number Measures of Variability ● Range: least useful ● Variance: ​average extent to which scores in a data set deviate from the mean (squared units, not easy to interpret) ● Standard deviation:​square root of variance (original units of data) ● Standard deviation and variance ○ On average, how far are scores from the mean? ○ High vs. low variability ● Normal distribution:normal curve ○ Most of the scores fall around the mean while fewer and fewer fall into the low and high end of the distribution ○ People are about average with only a few falling outside the norm ○ 68% are within 1 SD of the mean ■ 95% within 2 SD ■ 99% within 3 SD Skewed distributions ● Negative: most of the scores cluster at the higher end with a few outliers around the bottom ● Positive: most of the scores cluster at the lower end with a few outliers toward the top Z-Scores ● Identifies where a participant’s score falls in relation to the other participants ● Tells us how far a particular score is from the mean in standard deviation units Xi = participant’s score X = mean of the sample S = standard deviation of the sample


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