Managerial Statistic
Managerial Statistics
Distinguish between primary data and secondary data?
OBJECTIVE
The main objective of this topic is to measure the degree of relationship between the variables under consideration.The correlation analysis refers to the techniques used in measuring the closeness of the relationship between the variables.
DEFINITION
Some important definitions of correlation are given below:
1. “Correlation analysis deals with the association between two or more variables”. ---- Simpson & kafka.
2. “When the relationship is of quantitative nature, the appropriate statistical tool for discovering and measuring the relationship and expressing it in brief formula is known as correlation”.----- Croxton & Cowden.
3.Correlation analysis attempts to determine the “degree of relationship between variables”.----- Ya Lun Chou.
Thus correlation is a statistical device which helps us in analyzing the covariation of two or more variables.
TYPES OF CORRELATION
Correlation is described or classified in several different ways.Three of the most important ways of classifying correlation are:
1.Positive or negative 2.Simple, partial and multiple 3. Linear and non-linear
The various methods of studying correlation are
1.Scatter Diagram Method
2.Karl Pearson’s Coefficient of correlation.
3.Method of Least Squares [Of these , the first two methods shall be discussed as follows. ]
SCATTER DIAGRAM
What it is: A scatter diagram is a tool for analyzing relationships between two variables. One variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The pattern of their intersecting points can graphically show relationship patterns. Most often a scatter diagram is used to prove or disprove cause-and-effect relationships. While the diagram shows relationships, it does not by itself prove that one variable causes the other.
When to use it: Use a scatter diagram to examine theories about cause-and-effect relationships and to
Distinguish between primary data and secondary data?
OBJECTIVE
The main objective of this topic is to measure the degree of relationship between the variables under consideration.The correlation analysis refers to the techniques used in measuring the closeness of the relationship between the variables.
DEFINITION
Some important definitions of correlation are given below:
1. “Correlation analysis deals with the association between two or more variables”. ---- Simpson & kafka.
2. “When the relationship is of quantitative nature, the appropriate statistical tool for discovering and measuring the relationship and expressing it in brief formula is known as correlation”.----- Croxton & Cowden.
3.Correlation analysis attempts to determine the “degree of relationship between variables”.----- Ya Lun Chou.
Thus correlation is a statistical device which helps us in analyzing the covariation of two or more variables.
TYPES OF CORRELATION
Correlation is described or classified in several different ways.Three of the most important ways of classifying correlation are:
1.Positive or negative 2.Simple, partial and multiple 3. Linear and non-linear
The various methods of studying correlation are
1.Scatter Diagram Method
2.Karl Pearson’s Coefficient of correlation.
3.Method of Least Squares [Of these , the first two methods shall be discussed as follows. ]
SCATTER DIAGRAM
What it is: A scatter diagram is a tool for analyzing relationships between two variables. One variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The pattern of their intersecting points can graphically show relationship patterns. Most often a scatter diagram is used to prove or disprove cause-and-effect relationships. While the diagram shows relationships, it does not by itself prove that one variable causes the other.
When to use it: Use a scatter diagram to examine theories about cause-and-effect relationships and to