Prediction Using Simple Linear Regression

We calculate the predicted value of the dependent variable (Y) by inserting the estimated value of the independent variable (X) in the regression equation. The predicted value of the dependent variable (Y) is determined using the formula: $$\widehat{Y}=\widehat{b_{0}}+\widehat{b_{1}}X$$ Where: \(\widehat{Y}\)…

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Hypothesis Testing

Hypothesis testing is used to test whether the estimated regression coefficients are statistically significant. Hypothesis testing can be performed using the confidence interval approach or the t-test approach. In the previous learning objective, we discussed the confidence interval approach. In…

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ANOVA and Standard Error of Estimate in Simple Linear Regression

ANOVA is a statistical procedure used to partition the total variability of a variable into components that can be ascribed to different sources. It is used to determine the effectiveness of the independent variable(s) in explaining the variation of the…

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Analysis of Variance

Sometimes the simple linear regression model does not describe the relationship between two variables. To use regression analysis effectively, we must be able to differentiate the two cases. Breaking down the sum of squares total into its components. The sum…

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Assumptions of the Simple Linear Regression Model

Before we can draw conclusions, we need to make the following key assumptions. Linearity: A linear relationship exists between the dependent variable, Y, and independent variable X. Homoskedasticity: For all observations, the variance of the regression residuals is the same….

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Estimating the Parameters of a Simple Linear Regression

While conducting a regression analysis, we start with the dependent variable whose variation we want to explain and the independent variable that explains the changes in the dependent variable. The least-square criterion is used to measure the accuracy of a…

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Dependent and Independent Variables

Linear regression attempts to forecast the value of a dependent variable given the value of an independent variable. It assumes that there is a linear relationship between dependent and independent variables. A Simple Linear Regression relates a dependent and one…

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Study Notes for CFA® Level II – Financial Reporting and Analysis – offered by AnalystPrep

Study Session 5 Reading 11: Intercorporate Investment -a. Describe the classification, measurement, and disclosure under International Financial Reporting Standards (IFRS) for investments in financial assets, investments in associates, joint ventures, business combinations, and special purpose and variable interest entities; -b….

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Study Notes for CFA® Level II – Ethical and Professional Standards – offered by AnalystPrep

Reading 45: Code of Ethics and Standards of Professional Conduct -a. Describe the six components of the Code of Ethics and the seven Standards of Professional Conduct; -b. Explain the ethical responsibilities required of CFA Institute members and candidates in…

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Standard VI (C) – Referral Fees

Members and Candidates must disclose to their employer, clients, and prospective clients, as appropriate, any compensation, consideration, or benefit received from or paid to others for the recommendation of products or services. Guidance Members and Candidates are responsible for informing…

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