Lecture 6. univariate and bivariate analysis
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The document covers univariate, bivariate, and multivariate statistical analysis methods used in research methodology. It explains the types of variables and relevant statistical tests, including descriptive statistics for single and two-variable analyses. Additionally, it includes exercises to apply knowledge on degree of freedom and significance testing for chi-square results.
Lecture 6. univariate and bivariate analysis
- 1. Univariate and Bivariate Analysis Dr. Rajeev Kumar, M.S.W (TISS, Mumbai), M.Phil. (CIP, Ranchi), UGC-JRF, Ph.D. (IIT Kharagpur) Visiting Faculty, RKMVERI, Ranchi Lecture-6: Research Methodology (Descriptive and inferential statistics
- 2. After data collection We need to define the type of variables from the collected data. Based on the type of variables, we choose the appropriate statistical analysis
- 3. Types of statistical analysis Univariate: because it deals with single variable Bivariate: it deals with two variables Multivariate: it deals with more than two variables
- 4. Univariate analysis Descriptive analysis If categorical variables Mean (Standard Deviation) Median (IQR) Mode (Range) Frequency and percentage If continuous variables Central tendency Dispersion
- 5. Bivariate analysis Analytical statistics Chi square test T test Correlations and simple regression
- 6. Multivariate analysis ANOVA test Partial correlation Multiple and multivariate regression analysis
- 7. How to interpret the statistical result? Few examples • How the statistical results are displayed?
- 8. Display of sociodemographic profile (categorical variables)
- 9. Second example of descriptive data
- 10. Tables from research articles https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3105560/
- 11. Bivariate data
- 13. How to read these tables • We have to understand • What is DF (degree of freedom? • What is your ά alpha value? • What is p ( probability)? • What is the critical value? • What is the test value ?
- 14. What is df • Degree of freedom: The number of observation, which are free to vary or change.
- 15. Df for chi square
- 16. Table of critical values (Chi square)
- 17. What is our alpha value?
- 18. Now find out if your result is significant?
- 19. Exercise-1 • Please find out the DF (degree of freedom) • If one table has 5 column and 3 rows= • If table has 3 rows and 4 column = • If 3 column and 2 rows= • 3 column and 3 rows= • 2 column and 2 rows=
- 20. Exercise-2 • In one chi square analysis, df=2, Chi square χ2 = 4.03, tell me if this result is significant at .05? Whether this result is significant at .01 and .001? • In one survey the result of pass and fail was compared between male and female candidates, the chi square result reveals, df=1, χ2=1.89 now find out, whether this result is significant at p ≤0.05, p ≤ 0.01, and p ≤0.001 • In a chi square result, in the table, there were 4 columns and 4 rows. Calculate its degree of freedom. The test value of χ2 = 45.88, please evaluate this result at p ≤0.05, p ≤ 0.01, and p ≤0.001
- 21. Use this table again
- 22. Exercise-3: Now evaluate the chi square results
- 23. Thanks for your attention keep learning!!!