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## Foundations of Sociological Inquiry

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**Foundations of Sociological Inquiry**Statistical Analysis**Today’s Objectives**• Why use Statistics? • Descriptive Statistics • Inferential Statistics • Multivariate Techniques • Questions?**The formula Y = f(X) tells us that**• X is the dependent variable. • Y is the dependent variable. • f is the dependent variable. • need to know what Y, f, and X represent to determine the dependent variable. • None of these choices is correct.**Why Use Statistics?**Statistics enable us to construct simplified representations of a complex social world.**Why Use Statistics?**Statistics enable us to construct simplified representations of a complex social world. • Begin with a sociological question • Identify data to answer the question (collect, observe, record) • Analyze data (statistics help) • Present your findings (statistics help) • Situate your findings in relation to what we think we already know (statistics help)**Recommended Salary for Job Candidates:**$4000 $70,000 $40,000 $80,000 $120,000 $135,000 $70,000 $50,000 $67,000.00 $500,000 $50,000 $75,000.00 $60,000 $150,000 $20,000 $50000.00 $70,000 $80,000 $62,000 $200,000 95,000 $75000 $70,000 $80000 $75,000 $45,000 a year $100,000 $250,000 $65,000.00 $45000.00 $75,000 $88,000 $80,000.00 $150,000 $55,000 $130,000 $60,000 $78,000 $150,000 $50,000 70000 $45,000-60,000 $80,000 $75,000 $55000 $40,000 95,000 $80,000 $30,000.00 $80000 $30000 $70,000 $50,000 $50,000 $65000 $80,000 $? $80,000 $50000 $50000 (I have no idea how much Marketing Executive gets paid usually) 150,000 $74,000 $60,000 $60,000 $65,00 $80,000 $65,000 $90,000 $70,000 $90,000 $80,000 $45000 $45000 $35000 $100,000 $85,000 $50,000 $60000 80000 $85,000 $58000 $60000 $70,000 $80,000 $70,000 $40000 $70,000 $80,000 $60,000 $200,000 $80,000 $50000 $60,000 - $75,000 $80,000 $60,000 $45,000 $50,000 $90,000 $30,000 $60,000 50000 $200,000.00 $40000.00 $60000 $50,000 $75,000 $60000 $180000 $120,000 $80000 $55,000 $50,000 85000 $145,000 $ $85,000 $55,000 $70000 $75, 000 $60,000 60000 $ 10,000 $100000 $65000 $85,000 $80,000 $60,000 $ 70,000 $80,000 $75,000.00 $100,000 $50000.00 $70,000 $95,000 $92,000 $70,000 $50,000 $68,000 $80,000 $40,000 $30,000 $50,000 $60,000 $40,000 $80,000 $65,000 $i dont know $90,000 $60,000 $70,000 $80,000 $65000 $70,000 $ $100,000 $72000 $70,000 $50,000 $110,000.000 $80000 $18,000 $110,000 $200,000 $100,000 $80000**Descriptive Statistics (summary)**• Statistical computations describing either the characteristics of a sample or the relationship among variables in a sample • Data reduction • Measures of association • Regression analysis • Other forms of multivariate analysis**Difference in Means**• Is the difference in mean salary recommended by men and women statistically significant?**Difference in Means**• Is the difference in mean salary recommended by men and women statistically significant? • Conduct a t-test t = 0.20, df = 154, p-value = .84 95 percent confidence interval (-13392, 16512)**Difference in Means**• Is the difference in mean salary recommended by men and women statistically significant? • Conduct a t-test t = 0.20, df = 154, p-value = .84 95 percent confidence interval (-13392, 16512) • We should not reject the null hypothesis that the true difference in means is equal to zero**Multivariate Analysis**• Is the difference in mean salary recommended by men and women statistically significant, controlling for parental status of applicant?**Multivariate Analysis**• Is the difference in mean salary recommended by men and women statistically significant, controlling for parental status of applicant? • Conduct a regression analysis of recommended salary Variable Estimate t-value P-value Male Respondent -1452 -0.18 0.86 Parent Applicant -14018 -1.77 0.08+ Intercept 85846 13.18 <.001*****Multivariate Analysis**• Is the difference in mean salary recommended by men and women statistically significant, controlling for parental status of applicant? • Conduct a regression analysis of recommended salary Variable Estimate t-value P-value Male Respondent -1452 -0.18 0.86 Parent Applicant -14018 -1.77 0.08+ Intercept 85846 13.18 <.001*** • We should not reject the null hypothesis that the true difference in recommended salaries, controlling for parental status of applicant, is equal to zero**Inferential Statistics**• The body of statistical computations relevant to making inferences from findings based on sample observations to some larger population. • Sampling error • Non-sampling error**_____ indicate the likelihood that the relationship observed**between variables in a sample can be attributed to sampling error only. • Ex-post facto hypothesizing • Tests of statistical significance • Disconfirmation • Disambiguation**Statistical Significance**• Statistical Significance is a general term referring to the likelihood that the relationship observed in a sample could be attributed to sampling error alone.**Statistical Significance**• Statistical Significance is a general term referring to the likelihood that the relationship observed in a sample could be attributed to sampling error alone. • Tests of Statistical Significance are a class of statistical computations that indicate the likelihood that the relationship observed between variables in a sample can be attributed to sampling error alone.**Statistical Significance**• Statistical Significance is a general term referring to the likelihood that the relationship observed in a sample could be attributed to sampling error alone. • Tests of Statistical Significance are a class of statistical computations that indicate the likelihood that the relationship observed between variables in a sample can be attributed to sampling error alone. • Level of Significance, in the context of tests of statistical significance, the degree of likelihood that an observed, empirical relationship could be attributed to sampling error.**_____ are statistical measures used for making inferences**from findings based on sample observations to a larger population. • Descriptive statistics • Inferential statistics • Both of the above • Neither of the above**A statistical significance level of .05 means that**• the probability that a relationship as strong as the observed one can be attributed to sampling error alone is 5 percent. • we can be 5 percent sure that the relationship is real and not due to sampling error. • there is an .05 percent chance that a relationship as strong as the observed one can be attributed to sampling error. • the difference we observed in the table is 5 percent different. • there is a 5 percent standard error in the observations.