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PSYC 2301 (2)

PSYC 2301 Midterm: Test 3 Methods Review

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University of Houston
PSYC 2301
Foss Donald

Test 3 Methods Review New Topics to Cover  Correlation Facts o Difference Between Negative and Positive Correlation  Negative: linear relationship increases the values of one variable are accompanied by a decrease in the values of the other variable (Graph B pg 73)  Positive: Increase the values of one variable are accompanied by increases in the values of the second variable (Graph A pg. 73)  Scatter Plots o Graphic representation of each individual’s scores on two variables. The score on the first variable is found on the horizontal axis and scores on the second variable are found on the vertical axis o Single point in the diagram o Perfect positive relationship is +1.00 o Perfect negative is -1.00 o Pearson’s r correlation Coefficient  To calculate a correlation coefficient, we need to obtain pairs of observations from each subject  Individuals have two scores, one on each of the variables  The Pearsons r provides two types of information, strength of relationship and direction of relationship  Correlation is not the same as causation  CORRELATION COEFFICENT IS USED TO REPRESENT THE DEGREE OF RELATIONSHIP BETWEEN TWO VARAIBLES   Effect on correlation of “restricted range” o If the range of possible values is restricted, the magnitude of the correlation coefficient is reduced o With restricted range comes restricted variability in the scores and thus less variability that can be explained o Restriction of range: occurs when the individuals in your sample are very similar on the variable you are studying  Ex: If you are studying age as a variable, testing only 6 and 7 year olds will reduce your chances of finding age effects  Effect Size o Refers to the strength of association between variables  The Pearsons r correlation coefficient is one indicator of effect size; it indicates the strength of the linear association between two variables  Reliability and Validity: o How tests are assessed o Reliability: the correlation of the test with itself  The higher the correlation the higher the reliability  Low correlation is unreliably o Validity  The correlation of a test with external criterion  Higher the correlation, the higher the validity  Lower correlation is lower validity o A test has to be reliable to be valid o Reliability is necessary for validity  Inferential Stats o Population Vs. Sample  Inferential statistics are used to determine whether the results match what would happen if we were to conduct the experiment again and again with multiple samples  Population is what we want to know about so we select a sample from the population  Parameter: Population; Sample: Statistic  We care more about the parameter than the statistic  So we want to generalize from the sample to the population- to make an inference o The Decision Logic  The clai
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