1-to-1 : has rs with each other 1-to-many : have rs with one of them

Data is recorded over consistent intervals of time eg. GDP from 2000 - 2020

Variables + many observation at a single point / period of time eg. At year 2021 (all developing contires) are affected due to pandemic Example: 2020 US China Russia 他们分别的DV & IV

Time sereied + Cross sectional eg. Data of 2000 ~ 2020 (all selected countries / states / district) + DV & IV Example: 2020 - Malaysia, German, Australia 2019 - US, China, Russia 2018 - China, Malaysia, Thailand

Time Series + Cross Sectional eg. 2000 - 2020 (one country) of a respective event or group Example: Malaysia 1997 - Asian financial countries 2008 - Global financial crisis 2020 - Covid-19 Pandemic

Data Organisation

Data Transform

Data Cleaning

WDI, IMF, Dept. of stats

Predicted value of the independent variable (y) for any given value of the independent variable (x)

Intercept the predicted value of (y) when (x)=0

The regression coefficient - how muchwe expect (y) to change as (x) increases / decreases per unit

the independent variable (the variable to make predictions on y)

Error of the estimate - representing the difference between observed values & predicted values. Captures all other factors influencing (y) which are unobserved or unaccounted in the model

Multicollinearity = several independent variables in a model are correlated. Two variables are considered perfectly collinear if their correlation coefficient is +/- 1.0.

Acedasticity = occurrence of high intercorrelations among two or more independent variables

Autocorrelation = The degree of correlation of the same variables between two successive time intervals. It measures how the lagged version of the value of a variable is related to the original version of it in a time series

Each participant is only counted as one observation.

A probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. The normal distribution appears as a "bell curve" when graphed.

Bias = Disproportionate weight in favor of or against an idea or thing