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Statistical Description of Data Summary | Quantitative Aptitude for CA Foundation PDF Download

SUMMARY
Statistics deals with the aggregates. An individual, to a statistician has no significance except the fact that it is a part of the aggregate.
Statistics is concerned with quantitative data. However, qualitative data also can be converted to quantitative data by providing a numerical description to the corresponding qualitative data.
The theory of statistical inferences is built upon random sampling. If the rules for random sampling are not strictly adhered to, the conclusion drawn on the basis of these unrepresentative samples would be erroneous.
We can broadly classify data as
(a) Primary;
(b) Secondary.
Mode of Presentation of Data
(a) Textual presentation;
(b) Tabular presentation or Tabulation;
(c) Diagrammatic representation.
The types of diagrams:
(a) Line diagram or Historiagram;
(b) Bar diagram;
(c) Pie chart.
Frequency Distribution of a Variable
(a) Find the largest and smallest observations and obtain the difference between them, known as Range, in case of a continuous variable.
(b) Form a number of classes depending on the number of isolated values assumed by a discrete variable. In case of a continuous variable, find the number of class intervals using the relation, No. of class Interval X class length≅Range.
(c) Present the class or class interval in a table known as frequency distribution table.
(d) Apply ‘tally mark’ i.e. a stroke against the occurrence of a particulars value in a class or class interval.
(e) Count the tally marks and present these numbers in the next column, known as frequency column, and finally check whether the total of all these class frequencies tally with thetotal number of observations.

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FAQs on Statistical Description of Data Summary - Quantitative Aptitude for CA Foundation

1. What is a statistical description of data?
Ans. A statistical description of data refers to the process of summarizing and analyzing a set of data using various statistical measures such as mean, median, mode, standard deviation, and range. It helps in understanding the central tendency, dispersion, and patterns within the data.
2. How is the mean calculated in statistical description of data?
Ans. The mean is calculated by summing up all the values in a set of data and dividing the sum by the total number of values. It provides the average value of the data and is commonly used to represent the central tendency.
3. What is the significance of the median in statistical description of data?
Ans. The median is the middle value in a set of data when arranged in ascending or descending order. It is used to represent the central tendency and is particularly useful when the data contains outliers or extreme values that could affect the mean. The median provides a more robust measure of central tendency.
4. How does the standard deviation help in statistical description of data?
Ans. The standard deviation measures the dispersion or spread of data around the mean. It indicates how much the individual data points deviate from the average. A higher standard deviation implies greater variability in the data, while a lower standard deviation indicates greater consistency.
5. What does the range represent in statistical description of data?
Ans. The range is the difference between the maximum and minimum values in a set of data. It provides a simple measure of dispersion and represents the spread of data. However, it does not consider the distribution of values within the data and can be affected by outliers.
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