Math, asked by muskanrathore8833, 9 months ago

Explain correlation in statistics and precautions taken during use of statistics

Answers

Answered by pkanger
0

Answer:

The correlation can be explained in statistics by

the empirical relationship between the three measures of central tendency:

3 Median = Mode + 2 Mean

MEDIAN:

The mean (or average) of observation, as we know ,the sum of the values of all the observation divided by the total number of observations. The different methods for finding mean are :

Mean for Grouped method

Direct method

Assumed mean method

Step Deviation method

Precautions:

The result obtained by all three methods is the same. So, method to be used depends on the numerical values of xi and fi .

If xi and fi sufficiently small,then the direct method is an appropriate choice.

If xi and fi numerically large numbers, then we go for the assumed mean method or step deviation method.

If the class sizes are unequal , and xi are large numerically ,we can still apply the step deviation method by taking h to be suitable divisor of all the di ' s.

MODE:

A mode is that value among the observation which occurs most often I.e, the value of the observation having the maximum frequency.

Precaution:

It is possible that more than one value may have the same maximum frequency.In such situations, the data is said to be multimodal.

Though the grouped data can also be multimodal, we shall restrict ourselves to problem having a single mode only.

In a grouped frequency ,it is not possible to determine the mode by looking at the frequencies. Here, we can only locate a class with maximum frequency , called the modal class.

MEDIAN:

The median is a measure of central tendency which gives the value of the middle most observation in the data.

Precaution:

For finding the median of ungrouped data, we first arrange the data values of the observation in ascending order.

Then, of n is odd , the median is the {(n+1)/2}^th observation. And if n is even, then the median will be average of the (n/2)^th and the (n/2+1)^th observations.

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