ERP – System-Auditing, Device, Text and Job Management
IN addition to functions covered by technical modules such as user’s management, License management, installation (as discussed in earlier papers), ERP technical module provides several other important functionalities. Some of these functionalities, as given below, will be very briefly discussed in this paper: Audit management Device management Text management Job management Audit management: Large organizations […]
Role of External Consultants in Business Continuity Management
In previous articles, we have discussed how risk management teams and the management can help in planning for contingencies. In this article, we look at the role that external consultants can play in formulating and shaping a company’s business continuity planning. For starters, the biggest advantage that external consultants have over in house risk management […]
The Argentine Currency Crisis
The Argentine economy is no stranger to economic crises. The country saw a massive financial crisis with the currency almost collapsing in the year 2001. Now, seventeen years later, Argentina seems to be back to square one. Once again, the inflation rates in this Latin American nation have started skyrocketing. Also, the declining value of […]
China’s Wealth Gap Problem
Traditionally China has been one of the red states. This means that China traditionally adopted the policy of communism. Hence, one would expect the income and wealth disparity in China to be limited. However, surprisingly, that is not the case. China has one of the biggest wealth disparities in the world. For instance, the top […]
Why and When to avoid Holding Inventories
Every business organization that is engaged in manufacturing, trading or dealing with salable products holds inventories in one form another. Inventory is held in the form of raw materials or in the form of salable goods. Since every unit of inventoried item has an economic value and is itemized in the books of account of […]
The P-Value is a statistical representation of the likelihood that the null hypothesis is true. Therefore the P-Value is the probability that the output (Y) will not change as a result of the variation that we are deliberately introducing in the input (X).
Example: If we have a null hypothesis that says that there is no statistically significant relationship between the efficiency of workers in the New York factory as compared to the one in Sacramento California, then the P value attaches a probability to this statement.
If we say that for testing the following hypothesis we assign a P-Value of 0.05. This means that we are saying that 95 out of a 100 times, the efficiencies will not be different. Therefore we are admitting that 5% of the times they could be different. In this case the null hypothesis will only be rejected if we prove that differences in efficiencies arise let’s say 7% of the times.
The P-Value is an important part of the hypothesis problem. Changing the P-Values slightly can change which hypothesis is selected and which is rejected. Therefore the selection of the P-Value must be carefully done. There are different types of errors associated with choosing the wrong P Value. These errors have been described later. The management must decide which error they can afford to make before selecting the P-Value.
The P-Value and confidence interval are intertwined. In fact, if you have the value of one you can automatically derive the value of the other. The formula used in P value = 1 - Confidence Interval. Therefore for a P Value of 0.05, the confidence interval is 0.95 or 95%.
Statistical conclusions cannot be taken literally. One needs to carefully understand how to interpret them before any decisions are made which are based on them. For instance, we stated above that the null hypothesis stands true 95% of the time. Does this mean that if we were to conduct a 100 experiments right away, the null hypothesis would stand true 95 times or more? Well, not really.
Although this is what is ideally expected to happen, the entire subject of Statistics is based on the law of large numbers. This means that these conclusions can be tested for validity only after 1000’s of trials have taken place. When the numbers are sufficiently large, 95% will hold true!
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