Literature review

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OLS assumptions

  1. Linearity

  2. In continual sample Xi value is fixed. The regression model is taken for certain variables Xi are not derived stochastic and are not fixed in a continuous sample. Thus, conditional analysis depends on Xi variables.

  1. Homoscedasticity

Since the P-value=0.2410 is larger than 0.05 at 95% Significance level, the variance of Ui is constant for all observations.

  1. No autocorrelation

  1. Zero covariance

  1. The number of observations (N) has to be bigger than the number of determinant Xi variables.

  2. Difference in Xi values. According to correct prediction of Yi, Xi value should be numerical and varying.

  3. Correct specification.

The Ramsey test shows that at p-value=0.4747 greater than 0.05, the model does not contain any omitted variables.

  1. No perfect multicollinearity

Since the VIF=1.05 is higher than 0.1 and lower than 10, it is obvious that there is multicollinearity between Xi variables in the regression model.

Referance 2020. About The GSS | NORC. [online] Available at: [Accessed 12 March 2020].

CVA, K., 2017. Journal of Orthopedics & Bone Disorders, 1(7).

Scott-Clayton, S., 2020. The Tax Benefits For Education Don’T Increase Education. [online] Brookings. Available at: [Accessed 12 March 2020].

2020. [online] Available at: [Accessed 12 March 2020]. 2020. [online] Available at: [Accessed 12 March 2020].

Stevenson, P., n.d. Higher Education In Hong Kong: A Case Study Of Universities Navigatingthrough The Asian Economic Crisis.
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