Foundations of Sociological Inquiry

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# Foundations of Sociological Inquiry - PowerPoint PPT Presentation

## Foundations of Sociological Inquiry

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##### Presentation Transcript

1. Foundations of Sociological Inquiry Statistical Analysis

2. Today’s Objectives • Why use Statistics? • Descriptive Statistics • Inferential Statistics • Multivariate Techniques • Questions?

3. 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.

4. Why Use Statistics? Statistics enable us to construct simplified representations of a complex social world.

5. 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)

6. 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

7. 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

8. Recommended Salary for Job Candidates

9. Recommended Salary for Job Candidates

10. Difference in Means • Is the difference in mean salary recommended by men and women statistically significant?

11. 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)

12. 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

13. Recommended Salary for Job Candidates

14. Multivariate Analysis • Is the difference in mean salary recommended by men and women statistically significant, controlling for parental status of applicant?

15. 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***

16. 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

17. 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

18. _____ 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

19. 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.

20. 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.

21. 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.

22. _____ 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

23. 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.

24. Questions?