Psych 100.1H Focus QuestionsChapter 2 (pg. 37-end) & Appendix (A1-A8) – Class 49/4/20131. Define descriptive statistics. What are some common types of descriptive statistics and what information do they provide? How do descriptive statistics differ from inferential statistics?a. Summarizing sets of data. Mean, median, standard deviation. Set of marks indicating who showed a particular behavior and who didn’t, summarize the data by calculating percentage that showed it. 2. What statistic is calculated using inferential methods and how is this related to the idea ofstatistical significance? What factors affect statistical significance?a. Standard deviationb. Size of observed affect and number of individual subjects or observations and variability of data within each group3. How do error and bias differ? Which is considered more devastating for research and why?a. Error—random variability in results, random influences that increase variabilityb. Bias—nonrandom effects by a factor extraneous to research hypothesisc. Bias is more devastating because statistical techniques cannot correct for it. Error only reduces the chance that researchers will find statistically significant results. Bias can lead researchers to false conclusion that their hypothesis has been supported when a factor irrelevant to the hypothesis has caused results. 4. How are reliability and validity implicated in measurement bias? How can we assess the validity of a measure?a. Reliability—measurement error, not bias. Measure is reliable to the degree that it yields similar results each time it is used. b. Validity—lack of validity can be a source of bias. Valid if measures or predicts what it is intended to measure or predict. c. Common sense. Face validity. Correlate scores with one another. Criterion validity. 5. What are the three main considerations when conducting research with humans and why are these considerations important?a. Right to privacy: informed consent, anonymityb. Possibility of discomfort: advised free to quitc. Deception: reveal after
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