2. Regression Analysis
Regression is the study of the nature of relationship between the variable so that
one may be able to predict the unknown value of one variable for a known value
of another variable.
In regression, one variable is considered as an independent variable and another
variable is taken as a dependent variable.
Regression is the measure of the average relationship between two or more
variable. -M.M Blair
3. where:
where,
y is dependent variable.
M is slop
X is independent variable.
B Intercept.
The Regression line is a straight line that best fits the data, such that the overall distance from the line to the points (variable values)
plotted on a graph is the smallest.
“b” is the slope of the line
“a” is the y-intercept.
“x” is an explanatory variable.
“y” is a dependent variable
7. Linear Regression
It shows the relationship between a dependent variable and one or more
independent variables.
Used for predictive analysis.
8. Title and Content Layout with SmartArt
Simple Linear Regression:
Single Independent variable is
used to predict the value of
dependent variable
Multiple Linear Regression:
Multiple Independent variable
is used to predict the value of
dependent variable
13. Logistic regression
It is used for predicting the categorical dependent variable using a given set of
independent variable
It can be either Yes or NO and 0 or 1.
Mainly use for solving Classification problem
15. Correlation
A mutual relationship or connection between two or more things.
Example: Price and Demand
Correlation is statistical technique.
Used to measure degree and extent to which two variables fluctuate with
reference to each other.
Correlation means that between two series or groups of data there exist some
causal relationship. -W I King
19. Scatter Diagram
The scatter diagram is known by many names, such as scatter plot, scatter graph
and correlation chart.
This diagram is drawn with two variables,usually the first variable is independent
and the second variable is dependent on the first variable.
21. Graphical Method
In this method the individual values of variables X and Y are plotted on the graph
paper and two curves are obtained.
If the two curves move in the same direction it is an indication of positive
correlation
If the two curve move in the oppiste direction then correlation is said to be
negative.
This method is generally used when data is given over a period of time.
23. Karl Pearson’s coefficient
The Pearson correlation coefficient is very helpful statistical formula that
measure the strength between variables and relationship.
Also known as Pearson R test
