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MTH – Elementary Mathematics. LECTURE # 1. Introduction. 1. Recommended Books: musicmarkup.infote Mathematics with Applications (second edition) by. Elementary Mathematics (MTH). Handouts (pdf) / Powerpoint Slides (PPTs). Handouts / Power Point Slides. Lessons () (pdf Format). Course Codes. Download VU Elementary Mathematics - MTH Handouts. Elementary Mathematics - MTH musicmarkup.info VUTube. Administrator. Quote post.

What will be the percent decrease in the interest rate on a given balance? Stock represents a claim on the company's assets and earnings. As you acquire more stock, your ownership Virtual University of Pakistan Page docsity. Whether you say shares, equity, or stock, it all eans the same thing. Shares t not considered outstanding sto Net current asset value per share N btracting the total liabilities, and result by the total number of shares outstanding. NCAVPS is calculated by taking a company's current assets and su then dividing the Current Assets he value of all assets that are reasonably expected toT be converted into cash within one year in the arketable normal course of business.

Let us understand this point with the help of an example: In a technical college, it may well be the case that the ages of a group of first-year students are quite consistent, e.

A class of evening students undertaking a course of study in their spare time may show just the opposite situation, e. It is very clear from this example that the variation that exists between the various values of a data-set is of substantial importance.

We obviously need to be aware of the amount of variability present in a data-set if we are to come to useful conclusions about the situation under review. This is perhaps best seen from studying the two frequency distributions given below: The sizes of the classes in two comprehensive schools in different areas are as follows: If the arithmetic mean size of class is calculated, we discover that the answer is identical: Average class-size of each school.

And the graphs of the two distributions given below clearly indicate this fact. Absolute versus Relative Measures of Dispersion: There are two types of measurements of dispersion: An absolute measure of dispersion is one that measures the dispersion in terms of the same units or in the square of units, as the units of the data.

For example, if the units of the data are rupees, meters, kilograms, etc. On the other hand, relative measure of dispersion is one that is expressed in the form of a ratio, co-efficient of percentage and is independent of the units of measurement.

A relative measure of dispersion is useful for comparison of data of different nature. A measure of central tendency together with a measure of dispersion gives an adequate description of data. We will be discussing FOUR measures of dispersion i. The range is defined as the difference between the two extreme values of a data-set, i. For this reason it is used principally as a supplementary aid in the description of variable data, in conjunction with other measures of dispersion.

When the data are grouped into a frequency distribution, the range is estimated by finding the difference between the upper boundary of the highest class and the lower boundary of the lowest class. We now consider the graphical representation of the range:. Obviously, the greater the difference between the largest and the smallest values, the greater will be the range. As stated earlier, the range is a simple concept and is easy to compute.

However, because of the fact that it is computed from only the two extreme values in a data-set , it has two serious disadvantages.

From THIS point of view, it is an unsatisfactory measure of dispersion. It is interesting to note that the range can also be viewed in the following way: It is twice of the arithmetic mean of the deviations of the smallest and largest values round the mid- range i. Because of what has been just explained, the range can be regarded as that measure of dispersion which is associated with the mid-range. As such, the range may be employed to indicate dispersion when the mid-range has been adopted as the most appropriate average.

The range is an absolute measure of dispersion. This is a pure i. This is so because a pure number can be compared with another pure number. For example, if the coefficient of dispersion for one data-set comes out to be 0.

The quartile deviation is defined as half of the difference between the third and first quartiles i. It is also known as se Let us now consider the graphical representation of the quartile deviation:.

Although simple to compute, it is NOT an extremely satisfactory measure of dispersion because it takes into account the spread of only two values of the variable round the median, and this gives no idea of the rest of the dispersion within the distribution.

This is illustrated in the figure given below:. Let us now apply the concept of quartile deviation to the following example: The shareholding structure of two companies is given below:. Shares For comp Shares A comparison of the above two results indicate that there is a considerable concentration of shareholders about the MEDIAN number of shares in company Y, whereas in company X, there does not exist this kind of a concentration around the median.

From the above example, it is obvious that the larger the quartile deviation, the greater is the scatter of values within the series. The quartile deviation is superior to range as it is not affected by extremely large or small observations. It is simple to understand and easy to calculate. Purchase the AppleCare Protection Plan to extend. Gazebo telephone mama download Complete your Gazebo collection.

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