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Data Handling and Line Plots

Data refers to information. It can be a measure or numbers or some observations of things.

Data handlingis the process of ensuring whether data is stored, or archived in a safe and secure manner for a project.When you work on a project, you will arrive at the conclusions frome the data recorded.You can draw diagrams based on the data collected.

Examples:

Bar graphs, Pie charts, Pictograms, Line graphs.In these examples we use data handling.There are many methods in handling the data.Let us see them one by one.

The main use of Box and Whisker graph is to represent a given data in more informative manner so that we could easily judge by having a slit look of graph that where most of the numbers are.

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The word data means a set of given facts in numerical figures.Statistics is the science which deals with the collection, presentation, analysis and interpretation of numerical data.Here we discuss Fundamental Characteristics of Data, Types of Data, Raw or Ungrouped Data, Presentation of Data.

In Method forming classes of data, we discuss Rule To Convert Discontinuous (or Inclusive) Form To Continuous (or Exclusive) Form.

In Cumulative frequency of a Class interval, we see a few examples of Cumulative frequency and the Frequency distribution table.

Also, Preparing Frequency Distribution Table for raw data using tally is also discussed.

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Line Plots

The frequency of the data can be plotted using the number line with some symbols.

Hence, organizing the data in the simple way is much easier.Line plots are used to measure the frequency of an item in a dataset.

We discuss this using some solved examples.

Mean is the sum of the observation in the list divided by the total number of observations

The median is the middle value in a list ordered from smallest to largest.

The mode is the most frequently occurring value on the list.

In this topic we look at Mean of raw (ungrouped) data, Mean of grouped data, and Examples of Median and Mode.

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The word ‘population’ refers to a well defined set, aggregate or group of observations relating to a phenomenon under statistical investigation.The observations in populations may be any animal, commodities, people, ‘happenings’ of a particular type etc. So, we can have population of trees, insects, students, products etc.

Under this heading we discuss Population, Parameter and Statistic, Sampling Method, and Essentials of Sampling.

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