Sumários
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28 Setembro 2020, 14:30 • Rita Sousa
SUMMARY
Multiple linear regression is used to establish the linear relationship between a dependent and more than one explanatory variables; it is a generalization of the simple model. Students must be able to understand how the Ordinary Least Squares (OLS) method works, to compute and interpret the R^2, the adjusted R^2, the standard error of the regression, the F-test, the t-tests and confidence intervals for the parameters.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Multiple linear regression model |
Wooldridge, J. (2008), chapter 3 |
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24 Setembro 2020, 16:00 • Rita Sousa
SUMMARY
Correlation analysis can be used to quantify the linear association between two variables. Simple linear regression is used to establish the linear relationship between a dependent and one explanatory variable. Students must be able to interpret the scatter diagram, to compute and interpret the linear correlation coefficient and to estimate the parameters of the simple linear regression model.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Correlation and simple linear regression |
Wooldridge, J. (2008), chapters 1 and 2 |
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24 Setembro 2020, 14:30 • Rita Sousa
SUMMARY
Correlation analysis can be used to quantify the linear association between two variables. Simple linear regression is used to establish the linear relationship between a dependent and one explanatory variable. Students must be able to interpret the scatter diagram, to compute and interpret the linear correlation coefficient and to estimate the parameters of the simple linear regression model.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS and the following information:
|
SUBJECT |
BOOK/CHAPTER |
|
Correlation and simple linear regression |
Wooldridge, J. (2008), chapters 1 and 2 |
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17 Setembro 2020, 16:00 • Rita Sousa
SUMMARY
Statistical inference allows us to draw conclusions about the population from which the sample has been collected. The main tools of statistical inference are the CONFIDENCE INTERVALS and HYPOTHESES TESTING. Students must be able to deduce and interpret a confidence interval and to formulate and decide on hypothesis testing.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS.
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17 Setembro 2020, 14:30 • Rita Sousa
SUMMARY
Statistical inference allows us to draw conclusions about the population from which the sample has been collected. The main tools of statistical inference are the CONFIDENCE INTERVALS and HYPOTHESES TESTING. Students must be able to deduce and interpret a confidence interval and to formulate and decide on hypothesis testing.
STUDENTS AUTONOMOUS WORK
Students must read CLASS MATERIALS.