Business statistics - meaning, characteristics, functions and limitations
Business Statistics - Meaning, Characteristics, Functions and Limitations
The word Statistics seems to have been derived from the Latin word “status” or the Italian word Statista. All word means a political state. In early year “statistics” equipped a collection of facts about the people in the state for administration or political purpose.
Webster defined statistics as “the classified facts representing the conditions of the people in a state, especially those facts which can…
Diagrams and graphs - types, difference, uses and general rules of diagrams and graphs
Diagrams and Graphs - Types, Difference, Uses and General Rules of Diagrams and Graphs
Types of diagrams and Graphs:One of the most effective and interesting alternative way in which a statistical data may be presented is through diagrams and graphs. There are several ways in which statistical data may be displayed pictorially such as different types of graphs and diagrams. The commonly used diagrams and graphs to be discussed in subsequent paragraphs are given as under.
Types…
Short note on Measures of central tendency- mean, median and mode
Measure of Central Tendency - Mean, Median and Mode
A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position within that set of data. As such, measures of central tendency are sometimes called measures of central location. They are also classed as summary sstatistic:1. Mean2. Median 3. Mode
The mean, median and mode are all valid measures of central tendency, but under different conditions, some measures of cen…
Average (central tendency) and properties of good average
Average (Central Tendency) and Properties of Good Average
Average (Central Tendency)In the words of Croxton and Cowden, “An average value is a single value within the range of the data that is used to represent all the values in the series.”The value of average lies between the maximum and minimum values of the series. That is why it is also called measure of central tendency.
Properties of a Good AverageThe following are the important properties which a good average should sa…
Arithmetic mean (A.M) : properties, merits and demerits
Arithmetic Mean, Properties of Arithmetic Mean and Merits & Demerits of Arithmetic Mean
Arithmetic Mean: It is a value obtained by adding together all the items and by dividing the total by the number of items. It is also called average. It is the most popular and widely used measure for representing the entire data by one value.Arithmetic mean may be either:1. Simple arithmetic mean, or2. Weighted arithmetic mean.
Properties of Arithmetic Mean:1. The sum of deviations of …
Geometric mean - meaning, merits, demerits, and uses
Geometric Mean - Meaning, Merits, Demerits and Uses
Geometric Mean (G.M) It is defined as nth root of the product of n items or values.i.e., G.M. = n√ (x1. x2. x3 ……xn)
Merits of G.M.:1. It is not affected by the extreme items in the series.2. It is rigidly defined and its value is a precise figure.3. It is capable of further algebraic treatment.4. It is Useful in calculating index number.
Demerits of G.M.:1. It is difficult to understand and to compute.2. It cannot be computed…
Harmonic mean (H.M) : it's merits, demerits and uses
Harmonic Mean (H.M), its Merits, Demerits and Uses
Harmonic Mean: It is defined as the reciprocal of the arithmetic mean of the reciprocal of the individual observations.
Merits of H.M.:1. Like AM and GM, it is also based on all observations.2. It is most appropriate average under conditions of wide variations among the items of a series since it gives larger weight to smaller items.3. It is capable of further algebraic treatment.4. It is extremely useful while averaging certa…
Mode - meaning, merits and demerits
Mode - Meaning, Merits and Demerits
Mode: Mode is that value a dataset, which is repeated most often in the database. In other words, mode is the value, which is predominant in the series or is at the position of greatest density. Mode may or may not exist in a series, or if it exists, it may not be unique, or its position may be somewhat uncertain.
Merits of Mode:1. Mode is the most representative value of distribution, it is useful to calculate model wage.2. It is not affect…
Measure of dispersion - meaning, purpose, types and difference between absolute and relative measure of dispersion
Measure of Dispersion - Meaning, Purpose, Types and Difference between Absolute & Relative Measure of Dispersion
Dispersion is the measure of variation of items. It measures the extent to which the items vary from central value. Dispersion is also known as average of the second order.
In the words of Brooks and Dick,” Dispersion is the degree of the scatter or variation of the variable about a central value.”
In the words Simpson and Kafka,” The measurement of the Scatterne…
Range - Meaning, Merits and Demerits
Range - Meaning, Merits and Demerits
Range is defined as the difference between the value of the smallest item and the value of the largest item included in the distribution. It is the simplest method of measuring dispersion. Symbolically,
• Range= Largest value (L) – Smallest Value (S)
The relative measure corresponding to range, called the coefficient of range, is obtained by applying the following formula:
• Coefficient of Range= (L- S)/ (L S)
Meri…
Quartile Deviation (Q.D) - meaning, merits and Demerits
Quartile Deviation (Q.D) - Meaning, Merits and Demerits
Quartile Deviation: The QD is half of the difference between the upper and lower quartiles. Symbolically, QD= ½ (Q3- Q1)Quartile Deviation is an absolute measure of dispersion. The relative measure corresponding to QD, called the coefficient of QD, is obtained by applying the following formula:
Coefficient of Range= (Q3 - Q1) / (Q3 Q1)Coefficient of QD can be used to compare the degree of variation…
Mean Deviation (M.D) - Meaning, Merits, and Demerits
Mean Deviation (M.D) - Meaning, Merits and Demerits
Define Mean Deviation (M.D).Mention its merits and demerits.
Mean Deviation: For a given set of observation, MD is defined as the arithmetic mean of the absolute deviation of the observations from an appropriate measure of central tendency.The formula for computing MD isMD= ∑│D│/ N
MD is an absolute measure of dispersion. The relative measure corresponding to MD, called the coefficient of MD, is obtained by dividing mean devia…
Standard deviation and coefficient of variation
Standard Deviation and Coefficient of Variation
Standard Deviation: The standard deviation commonly denoted by ‘σ’ (Sigma) is the most widely used measure of dispersion. It is the square root of the second moment of dispersion and is calculated from the arithmetic mean. In short, it may be defined as the root-mean-square deviation from the mean.
Merits of Standard Deviation:1. It is based on each and every item of the data and it is rigidly defined.2. It is capable of further …
Regression analysis
Regression Analysis
Regression is the measure of the average relationship between two or more variable in terms of the original units of the data. It is a statistical tool with the help of which the unknown values of one variable can be estimated from known values of another variable.
Kinds of RegressionKinds of Regressionmay be studied on the basis of: 1. Change in proportions2. Number of variation
1. Basis of Change in Proportion: There are two important regressions on the ba…
Correlation analysis: meaning, kinds, uses, limitations and degrees of correlation
Correlation Analysis: Meaning, Kinds, Uses, Limitations and Degrees of Correlation
Correlation is the degree of the relationship between two or more variables. It does not explain the cause behind the relationship.
Kinds of Correlation may be studied on the basis of:I. Change in proportion.II. Number of variation.III. Change in direction.
(I) Basis of change in proportion: There are two important correlations on the basis of change in proportion. They are:(a) Linear correlation…
Methods of correlation
Methods of Correlation
The different methods of studying relationship between two variables are: 1. Scatter diagram method.2. Graphic method3. Karl Pearson’s coefficient of correlation4. Rank correlation method
1. Scatter Diagram Method: It is a graphical representation of finding relationship between two or more variables. Independent variable are taken on the x-axis and dependent variable on the y-axis and plot the various values of x and y on the graph. If all values move u…
Regression lines
Regression Lines
A line of regression by the method of “least square” shows an average relationship between variables under study. This regression line can be drawn graphically or derived algebraically. A line fitted by method of least square is known as the line of best fit. There are two regression lines:-
Regression line of x on y: Regression line of x on y is used to predict x for a given value of y. The regression equation of x on y is x=a by.
Regression line of y on x: Re…
Index number: meaning, features, advantages, limitations and problems in the construction of index number
Index Number: Meaning, Features, Advantages, Limitations and Problems in the Construction of Index Number
Introduction: Index number is an indicator of changes in prices and quantities. It is a specialized average designed to measure the change in a group of related variables over a period of time. It is also an indicator of inflationary or deflationary tendencies.
Features of Index Number: Following are the various feature of index number:1. Measures of relative changes: Inde…
Cost of living index number(CLI)
Cost of Living Index Number (CLI)
Cost of living index numbers generally represent the average change in prices over a period of time, paid by a consumer for a fixed set of goods and services. It measure the relative changes over time in the cost level require to maintain similar standard of living.Items contributing to consumer price index are generally:• Food• Clothing• Fuel and Lighting• Housing• Miscellaneous.
Uses of Cost of Living Index:1. CLI numbers are used for adjust…
Time series analysis- meaning. Utilities, components and model of time series analysis
Time Series Analysis - Meaning, Utilities, Components and Model of Time Series Analysis
Introduction: A time series is a set of statistical observations arranged is chronological order. Time series may be defined as collection of magnitudes of some variables belonging to different time periods. It is commonly used for forecasting.
Utilities of Time Series Analysis1. It helps in understanding past behaviour and is useful for prediction of future.2. It facilitates comparison.3. …
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