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Descriptive Statistics

Descriptive Statistics. Variable - something that can vary or change Dependent variable - something we measure Data - a collection of measurements Statistics - summary descriptions of data (i.e., mean, medium, range). Descriptive Statistics.

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Descriptive Statistics

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  1. Descriptive Statistics • Variable - something that can vary or change • Dependent variable - something we measure • Data - a collection of measurements • Statistics - summary descriptions of data (i.e., mean, medium, range)

  2. Descriptive Statistics • Used to describe or summarize sets of data to make them more understandable • measures of central tendency • mean, median, mode • measures of variability • range, standard deviation • measures of association • correlation coefficient

  3. Measures of Central Tendency • What is the average family income above? • Mean - the arithmetic average • Median - the center score • Mode - the score that occurs the most

  4. Measures of Variability • Range - the difference between the highest and lowest score in a set of data • Standard deviation - reflects the average distance between every score and the mean

  5. Correlation Coefficient • Often we measure more than one variable • Grade point and SAT score • Are they related? • Correlation statistic is a way to find out

  6. Correlation Coefficient • Measures whether two variables change in a related way • Can be positive (max +1.00) • Negative (min -1.00) • Or not related! (~ 0.0)

  7. Inferential Statistics • Descriptive statistics summarize a data set • We often want to go beyond the data • Is the world at large like my sample? • Are my descriptive statistics misleading? • Inferential statistics give probability that the sample is like the world at large

  8. Statistics and Probability • Probability means how likely something is • How likely are results like mine to occur by chance? • Statistical inferences • significant result - reflects the real world rather than chance, with high probability (e.g., > .95 ) • not significant - results reflect chance

  9. Measurement Errors • Why is inference based on probability instead of certainty? • Data can be misleading because of variability • low variability • high variability

  10. Measurement Errors • Why is inference based on probability instead of certainty? • Data can be misleading because of bias • low bias • high bias

  11. Variability Bias Variability & Bias Measurement Error • Variability and bias can combine

  12. Sources of Bias • Biased sample - when the members of a sample differ in a systematic way from the larger population the researcher is interested in • Example • interested in all voters • contact by telephone • biased sample - lower economic groups may not own telephones

  13. Sources of Bias • Observer-expectancy effect • researcher has expectations that influence measurements • Subject-expectancy effect • subject knows design and tries to produce expected result • Blinding • minimize expectancy by removing knowledge about experimental conditions

  14. Blinding • Single-blind study - when subjects are kept uninformed as to the treatment they are receiving • Double-blind study - when both subjects and experimenter are kept uninformed about aspects of the study that could lead to differential expectations

  15. Ethical Issues in Psychological Research • Right to privacy • Informed consent • use of deception • Animal rights • Is there justification for discomfort or harm a research procedure may produce? • APA publishes ethical guidelines

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