Question

(1) what examples specifically in the area of Probability Theory can you provide relating to economics and finance?

(2) state the independent and dependent variables for regression analysis,  give examples.

Answer 1

Answer 1.)

Probability is the likelihood of the happening of an even during a given period of time. In other words, it is a numerical measure that tells that a particular event would happen. The value of probability lies mostly between 0 and 1.

Probability and Economics:

As the field of economics mainly deals with the numerical data, so , the presence of probability technique is a must in order to analyze or conclude a given economic scenario.

One of the most important sub-branch of probability is the "Probability distribution" which is heavily used in economics in order to draw the inference about the variable in the data and thus it is further used for conclusion by the policymaker for making fiscal and monetary policies.

Similarly, the t-test, z-test and many other tests given by the statisticians are used in Economics in order to check whether a variable in question is significant or desirable for carrying out the analysis.

Probability in Finance:

Finance is the mainly study of financial instruments such as bonds, stocks including the interest rates and many other financial parameters in an economy during a given period of time. In other words, finance is used in order to determine the financial health of an economy.

In finance, a probability distribution(confidence interval) can be used in order to find the range within which the stocks may vary. A financial analyst can also use the past historical data of bonds, stocks, etc to estimate the probability by which the stocks, bonds may rise or decline in the coming days.

In other words, the probability approach can be used in Finance in order to predict the rate of change in the price of stocks, etc.

Answer 2.)

The dependent variable is the variable whose value depends upon the other variables and it changes as the other variable is changed.

Independent variables are those variables in the regression analysis whose value is not changed in the analysis and is rather used to find the dependent variable.

Example:

As we can see in the below equation, on the L.H.S we have the "x" variable, and on R.H.S, we have the "y" variable. Here, we would change the value of "y" in order to find the corresponding value of "x".

x = 7 + 2y

So, "x" is the dependent variable as its value depends upon the "y".

And, "y" is the independent variable as its value does not depend on any other variable.