Branch of mathematics concerned with collection, classification, analysis, and interpretation of numerical facts, for drawing inferences on the basis of their quantifiable likelihood probability.
Statistics can interpret aggregates of data too large to be intelligible by ordinary observation because such data unlike individual quantities tend to behave in regular, predictable manner. It is subdivided into descriptive statistics and inferential statistics. It will help you to understand the question paper pattern and type of statistics for management question and answer asked in MBA 1st year statistics for management exam.
In the above article, a student can download statistics for management notes for MBA 1st year and statistics for management notes for MBA 1st semester. Statistics for Management study material includes statistics for management notes, statistics for management books, statistics for management syllabus, statistics for management question paper, statistics for management case study, statistics for management questions and answers, statistics for management courses in statistics for management pdf form.
Come on! Save my name, email, and website in this browser for the next time I comment. Skip to content Post last modified: 9 April Reading time: 6 mins read. Download PDF. Sharing is caring More. Leave a Reply Cancel reply Comment. Enter your name or username to comment. Enter your email address to comment. The X-axis is an asymptote to the curve. It is unimodal distribution. Mean, Mode and Median coincide. The area under normal curve within certain limits is depicted in table 3. The graphical representation is depicted in figure 3.
B : In a sample of workers in a factory, the mean and standard deviation of wages were Rs Find the percentage of workers getting wages between Rs. Describe in brief all such steps. It is a tentative explanation of the research problem or a guess about the research outcome.
To test a hypothesis means to tell on the basis of the data researcher has collected whether or not the hypothesis seems to be valid. Having calculated appropriate z-statistic or t-statistic, to reject or accept the null hypothesis, it is necessary to identify the rejection region with reference to the given level of significance. If the calculated statistic is in the rejection region, we accept the alternative hypothesis against the null hypothesis at that level of significance.
Otherwise we accept null hypothesis at the given level of significance. Table 3. Step 3: Select the appropriate test from the list given in table 3. Step4: Calculate the required values for the test. Step 5: Conduct the test. Step 6: Draw conclusion.
Q3 b Distinguish between: Stratified random sampling Systematic sampling This sampling design is most appropriate if the This design is recommended if we have a population is heterogeneous with respect to complete list of sampling units arranged in some characteristic under study or the population systematic order such as geographical, distribution is highly skewed.
Provides more efficient estimate It gives biased results if periodic feature exist in the data Can be applied in situation where different More efficient than simple random sampling if degrees of accuracy is desired for different we have up-to-date frame.
It is the most suitable method if the population It is used to make pilot studies. Correlation Analysis: When two or more variables move in sympathy with the other, then they are said to be correlated. According to A. Regression analysis is used to get a measure of the error involved while using the regression line as a basis for estimation.
B How does correlation analysis differs from regression analysis? In regression analysis, it is attempted to quantify the dependence of one variable on the other. Correlation and regression analysis are related in the sense that both deal with relationships among variables. In order to be assured of the coming course of events, an organised system of forecasting helps. There are two aspects of Scientific Business Forecasting 1.
Analysis of past economic conditions. Analysis of present economic conditions. B Methods Of Business Forecasting: Almost all businessmen forecast about the conditions related to their business.
In recent years scientific methods of forecasting have been developed. The base of scientific forecasting is statistics. To handle the increasing variety of managerial forecasting problems, several forecasting techniques have been developed in recent years. The following are the main methods of business forecasting. Business Barometers: Business indices are constructed to study and analyse the business activities on the basis of which future conditions are predetermined.
With the help of these business barometers the trend of fluctuations in business conditions are understood and a decision can be taken relating to the problem by forecasting. Time series analysis: Time series analysis is also used for the purpose of making business forecasting.
The forecasting through time series analysis is possible only when the business data of various years are available which reflects a definite trend and seasonal variation. By time series analysis the long term trend, secular trend, seasonal and cyclical variations are ascertained, analysed and separated from the data of various years.
Extrapolation: Extrapolation is the simplest method of business forecasting. By extrapolation, a businessman finds out the possible trend of demand of his goods and also about the future price trends.
Regression analysis: The regression approach offers many valuable contributions to the solution of the forecasting problem. It is the means by which we select from among the many possible relationships between variables in a complex economy, which will be useful for forecasting.
Modern econometric methods: Econometric techniques, which originated in the eighteenth century, have recently gained popularity for forecasting. Econometrics refers to the application of mathematical economic theories and statistical procedures to economic data to verify economic theorems.
Models take the form of a set of simultaneous equations. The values of the constants in such equations are supplied by a study of statistical time series, and a large number of equations may be necessary to produce an adequate model. Exponential smoothing method: This method is regarded as the best method of business forecasting as compared to other methods. Exponential smoothing is a special kind of increasing exponential weighted average assigned to recent observation data and is found extremely useful in short-term forecasting of inventories and sales.
C Theories of Business Forecasting: There are a few theories that are followed while making business forecasts. Some of them are: 1. Sequence or time-lag theory: This is the most important theory of business forecasting. It is based on the assumption that most of the business data have the lag and lead relationships, that is, changes in business are successive and not simultaneous.
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