Psych 301 9 5 3 Data Analysis Quality of Data Validity The extent to which the data collected measure the intended variable Error Effects due to variables other than those measured NOT just noise or mistakes includes e g variation among individuals 2 types Random and Systematic Random Error Amount is different on each measurement Tends to average out to zero over time or individuals Reliability lack of random error consistency Systematic Error Same effect on every measurement Does not average out Produces confounds Accuracy lack of systematic error Descriptive Statistics Measures of Central Tendency Mean Median Mode Measures of Variability Range Standard Deviation Relationship between two variables Correlations Scatterplot The correlation coefficient Strength of relationship 0 0 to 1 0 Direction of relationship Positive vs negative correlation Assumes linear relationships Null vs alternative hypotheses Null Hypothesis H0 Default hypothesis States that no effect exists 0 correlation between 2 variables or no difference between 2 groups Alternative Hypothesis H1 The real hypothesis States that there is an effect Always the logical opposite of H0 Goal of most research is to reject H0 and allow adoption of H1 Statistics Population the group of people events a theory applies to Sample the people events observed in a particular study Goal is to learn about population but we only have access to sample Random error in data means there will always be some effect in the sample even when not present in population Inferential statistics Help determine whether effect is present in population real or simply due to chance Compare observed effect to what is likely due to chance alone Relies critically on amount of random error in data Significant vs nonsignificant differences p value probability that observed effect would occur by chance alone level cutoff used for p usually 5 Statistically significant effect p effect is bigger than would be likely by chance can reject H0 and tentatively accept H1 Non significant effect p Effect could have happened by chance Cannot reject H0 need further research Evaluating research Is there a theoretical basis for the work Appropriate methods and levels of analysis Adequate operational definitions Appropriate evidence of causal relationship Careful experimental design and control To what populations do the results apply
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