Glossary of Psych Statistics
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- Descriptive Statistics
- method for organizing and describing experimental data
- Inferential Statistics
- method for making decisions about the significance of experimental results. were the results caused by the IV or just by chance
- the cumulative frequency. the number of scores at or below any given score
- the proportion of scores at or below any given score ( take the cumf and divide by the total number of scores)
- percentage of scores at or below any given score
- the data (scores) arranged from lowest to highest
- the frequency with which each score occurs in the data
- mathematical average of a group of scores, the sum of the scores divided by the number of scores
(most vulnerable to extreme scores)
- the middle score, at the 50%ile where 1/2 the scores are above and 1/2 the scores are below(best used for skewed distributions)
- the simplist measure. the difference between the highest and lowest scores in the distribution
- the difference between a given score and the mean of the distribution D=x - xbar
- the square of a scores deviation from the mean d2=variance.
- standard deviation
- the avergae deviation of all scores from the mean
- calculating standard dev.
- 1. find mean of distributon
2. create freq. dist. chart
-d(deviation, the score-mean)
-d2(variance, deviation squared)
-fd2(variance * freq)
1 add up all the numbers in fd2
2 divide dum of fd2 by N
3 take square root of result
- Normal frequency distribution
- symmetrical all around
- skewed to right or left. either few extremly high scores or a few extremly low scores
- s-shaped curve. either all high scores or all low scores.
- m-shaped. has two modes.
- U-shaped. extreme scores on both ends.
- small standard dev. (scores all bunched up around mean)
- large standard deviation (scores very spread out)
- classic shape. Standard normal curve.
+1, +2, +3 numbers
- percentiles can also be seen as...((13.59%))
- probabilities ((P=.1359))
- z-score defintion
- allows us to determine the exact distance of any given score from mean (in standard deviations). All you need is the mean and stand. dev.
- z-score formula
- z= (x-xbar)/ standard dev.
- example of z-score
IQs=140 xbar= 200 SD=30
IQmj=60 xbar=30 SD=10
- refers to the type and the strength of the relationship between two variables. Correlation data does not indicate a cause and effect relationship.
- correlation coefficient
- Pearson's r
+1=perfect/direct + rel.(Aup B up)
-1=perfect/indei2rec/inverse/- relationship (Aup B down)
- Logic of inferential statistics
- to decide if the difference between the experimental group mean and the control group mean was caused by the IV or just chance
- Null Hypothesis (Ho)
- Nearly always define the Ho as follows "the difference between the xbar"e" and the xbar"c" is caused due to chance" (Assumption/Theory)
- Ho is correct
Fail to reject the Ho
- assert difference is due to chance
- Ho is incorrect
Reject the Ho
- assert difference is caused by IV
- alpha level
- the probability of an event occuring by chance at which one is willing to reject the Ho
- p=1 of 100 times (by chance)
- p= 5 of 100 times (by chance)
- if Xbar"e" < alpha...
- reject Ho
caused by IV
- if xbar"e" > alpha...
- fail to reject the Ho
caused by chance
- diff between descriptive/inferential
- make decisions with inferential andnot with descriptive. describe with descriptive
- if r=+1.00 and variable A is decreasing what is happening to variable b
- also decreasing
- mean is 10. sd is 2. what is score at z=+2
- cumulative freq.
- number of scores @ or below or @ and above
- type 1 error
- increases as alpha increases=rejecting the ho when it is true=stating IV caused the result when it was really due to chance
- type 2 error
- increases as alpha gets smaller=failing to reject t he Ho when it is really false=stating the result was due to chance when was due to IV
- stat. use for multiple IV's
- students t
- used when control group represents the entire pop.
- correlation between IV and DV= helps detect interactions between variables
- compares observed outcomes(data) with expected outcomes (Ho)
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