Скачать или смотреть Biostatistics: Correlation and Linear Regression, Part 6,Interesting Video Lecture in Amharic Speech

Biostatistics: correlation and linear regression, part 6,is lectured using Amharic language speech with detailed explanations. This video lectures the details of correlation and linear regression, correlation, linear regression, Pearson correlation coefficient, rank correlation coefficient, scatter plots and correlation, correlation coefficient,estimation of correlation coefficient, SPSS / STATA correlation analysis output, linear regression,linear regression analysis or model, dependent/ outcome variable, independent variables, simple linear regression, regression analysis, dummy variables, simple linear regression model, linear function, equation of the fitted line, α intercept, β slope, fitting linear regression line, estimating the regression coefficients, method of least squares, least squares criterion and equation, interpretation of the slope and the intercept, steps in regression analysis, examples of simple linear regression, estimation using the computational formula, linear regression in SPSS, explained and unexplained variation, coefficient of determination, R2, inference about the slope: f-test & t-test, CI estimation, graphical display of simple linear regression, residual analysis and R-square, how good is the linear model, P-values and significance levels,importance of the residual analysis, linear regression assumptions/ model diagnostics, linear relationship, normality, independent observations, equality of variance, fixed independent variables, no outlier distortion, no multicollinearity, representative sample and proper specification of the model (no omitted variables), multiple linear regression, multiple linear regression model, partial regression coefficients, tests on individual regression coefficients, scatter plot, interpretation of linear regression on spsss and stata outputs, analysis of residuals, model diagnostic tests, multi-collinearity/ inter-correlation, detecting and handling multi-collinearity, variance inflation factors (VIF),examples of multiple linear regression in SPSS and STATA,examples, exercises, their solutions, SPSS results, STATA results, all formulas of the unit, and sound research article examples for all mentioned components.
Unit 1: Introduction to biostatistics, Unit 2: Descriptive statistics, Unit 3: Demography and health service statistics, Unit 4: Probability and probability distributions, Unit 5: Sampling methods and sample size determination, Unit 6: Statistical inference / Estimation and hypothesis testing, Unit 7: Analysis of variance (ANOVA), Unit 8: Regression and correlation, Unit 9: Categorical data analysis, Unit 10: Survival data analysis, Unit 11: Count data analysis, and Unit 12: Introduction to Software (SPSS, STATA, Epi Info, R, etc.).
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