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What level(s) of measurement is the frequency distribution designed to describe? |
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In a bar graph the 'bars': |
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In a histogram the 'bars': |
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What level(s) of measurement is a bar graph designed to describe? |
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What level(s) of measurement is a histogram designed to describe? |
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bell-shaped one peak with two tails right side is mirror image of left |
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2 peaks (set of clusters) |
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Uniform (flat) distribution |
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roughly the same # for every attribute |
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What are the measures of central tendency? |
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"the average" "the value around which all deviations sum to zero" great measure; use it when you can designed for ratio level measures highly influenced by skewness and outliers -still mathematically correct -but can be misleading |
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• the attribute falling in the middle of a rank ordered set of scores • attribute that falls at the 50th percentile • EX- data from 7 people in rank order (odd number) 0,0,1,2,3,7,8 median= attribute at 4th position (2) • EX- data from 8 people in rank order (even number 0,0,1,2,3,7,8,10 median=average of 4th & 5th positions • average of 2 and 3= 2.5 median • not as functional as the mean • Not sensitive to outliers/skewness • The variable must be ordinal or ratio (must put attributes in rank order; you cant rank nominal) |
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• simplest measure of central tendency • the attribute that occurs most often (has the highest frequency) NOT how many times it occurs • Not as functional as the median (or mean) • A variable can have more than 1 (bi-modal) • Not sensitive to outliers/skewness • The only central tendency measure you can use with nominal data |
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what are the measures of variability? |
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range standard deviation variance |
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o -simplest measure o -Range=highest-lowest o -Larger range=more variability -Weakness of the range -Sensitive to outliers -ignored the variability of the scores “in the middle” |
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What are the 3 criteria for determining causality? |
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temporal order correlation rule out spuriousness |
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What does random assignment mean? |
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Randomly assigned to control group/experimental group |
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what do measures of central tendency do? |
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# that tells us where a variables attributes tend to fall |
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make a football fatter
pearson r will be lower (i.e.- weaker) b/c of its outlier |
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make football skinnier
pearson r will be higher (i.e. stronger) b/c of this outlier |
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3 rules for using the measures of central tendency |
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1. use mean whenever appropriate -ratio data that is normally distributed (or approximately normal)
2. if you cant use the mean, use the median (if appropriate) -ordinal data, or ratio data that are highly skewed or have outliers
3. if you cant use the median use mode -when you have nominal data |
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"double blind" experiments |
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-participants dont know what group they are in -researcher collecting/analyzing data doesn't know -3rd party knows but doesn't reveal info until data are analyzed |
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statistically significant |
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does not necessarily mean big instead it says the finding is REAL, we believe it exist in our population |
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a table showing the correlation between all possible combinations of variables
univariate analysis/statistics- 1 variable bivariate analysis/statistics- 2 variables multivariate analysis/statistics- 3+ variables |
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is the loss of participants over time due to refusal to participate, inability to reestablish content, death, etc. |
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