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free smude BBA Semester 1 assignments answer for BBA104 Q1.What do you mean by Measures of Central Tendency? Explain the Measures of Central Tendency.

Answer:  A single number describing some features of a frequency distribution is called descriptive statistics. There are various ways in which frequency curves can differ from one another. Even though the ‘general’ shapes of the curves are the same (the area under them is already made equal by the strategy of plotting the percent density), the details of the shape may change.Thus, a kind of an ‘average’ location of the distribution along the variable
axis is an important descriptive statistics. These statistics are collectively known as measures of location or of central tendency. Since a typical value usually occupies a central position, so that some observations are larger and some others are smaller than it, and termed as averages or measures of central tendency.

There are three measures of central tendency-Mean, Median, and Mode.
Again Mean is of three types: 
1.    Arithmetic Mean (A.M),
2.    Geometric Mean (G.M), and
3.    Harmonic Mean (H.M).
The words ‘mean’ and ‘average’ only refers to Arithmetic Mean.

Mean

The mean is also known as the average. Most of us look at an average as a way of smoothing over the variations in data and obtaining a single representative number.

Arithmetic Mean

Arithmetic Mean is the most widely used measure of central Tendency. Arithmetic mean is defined as the ratio between the sum of the observations and the number of observations. Arithmetic mean can be computed in two ways: i) Simple arithmetic mean, and ii) Weighted arithmetic mean. In case of simple arithmetic mean, equal importance is given to all the observations while in weighted arithmetic mean, the importance given to various observations are different.

Geometric mean

Let the number of observations are n. The geometric mean is a measure of central tendency which is equal to the nth root of the product of the observations. The formula for the geometric mean (GM) is:

GM=(X1X2X3……Xi…..Xn)1/n, where Xi is the ith observation.

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