Simple Linear Regression
, Regression Analysis
• In 1889, Sir Francis Galton, a cousin of Charles Darwin
published a paper on heredity, “Natural Inheritance”.
• It refers to the statistical technique of modeling the
relationship between two or more variables. In general
sense, regression analysis means the estimation or
prediction of the unknown value of one variable from the
known value(s) of the other variable(s).
• It is one of the most important and widely used statistical
techniques in almost all sciences - natural, social or physical.
, Simple Linear Regression
• Regression analysis is a mathematical measure of the average
relationship between two or more variables in terms of the
original units of the data.
• Study the nature of relationship between the variables.
Establish if there is a statistically significant relationship
between two variables
• The cause and effect relationship is clearly indicated through
regression analysis
• Forecast new observations-
ex- what will be the sales of mask over the next quarter?
, Simple Linear Regression
• In regression analysis we use the independent variable (X) to estimate the
dependent variable (Y).
• Dependent variable: This is the variable whose values we want to explain
or forecast . Its values depend on something else. We denote it as Y
• Independent variables: This is the variable that explains the other explain
variable . Its values are not dependent, called independent variable. We
denote it as X.
• Both variables must be at least interval scale.
• The relationship between the variables is linear.
You may remember the equation
y=mx+c
y= a+bx
, Regression Analysis
• In 1889, Sir Francis Galton, a cousin of Charles Darwin
published a paper on heredity, “Natural Inheritance”.
• It refers to the statistical technique of modeling the
relationship between two or more variables. In general
sense, regression analysis means the estimation or
prediction of the unknown value of one variable from the
known value(s) of the other variable(s).
• It is one of the most important and widely used statistical
techniques in almost all sciences - natural, social or physical.
, Simple Linear Regression
• Regression analysis is a mathematical measure of the average
relationship between two or more variables in terms of the
original units of the data.
• Study the nature of relationship between the variables.
Establish if there is a statistically significant relationship
between two variables
• The cause and effect relationship is clearly indicated through
regression analysis
• Forecast new observations-
ex- what will be the sales of mask over the next quarter?
, Simple Linear Regression
• In regression analysis we use the independent variable (X) to estimate the
dependent variable (Y).
• Dependent variable: This is the variable whose values we want to explain
or forecast . Its values depend on something else. We denote it as Y
• Independent variables: This is the variable that explains the other explain
variable . Its values are not dependent, called independent variable. We
denote it as X.
• Both variables must be at least interval scale.
• The relationship between the variables is linear.
You may remember the equation
y=mx+c
y= a+bx
