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Why are graphs important in statistics?
Graph are useful tools in that they organize data, so the information becomes clearer. This organized information can then be used to craw conclusions, to make decisions, or to influence others. There is also the need to have the ability to read and interpret statistical process control charts.
Why are graphs used in statistics?
Good graphs convey information quickly and easily to the user. Graphs highlight the salient features of the data. They can show relationships that are not obvious from studying a list of numbers. They can also provide a convenient way to compare different sets of data.
What is the importance of graph?
Graphs are a common method to visually illustrate relationships in the data. The purpose of a graph is to present data that are too numerous or complicated to be described adequately in the text and in less space. Do not, however, use graphs for small amounts of data that could be conveyed succinctly in a sentence.
Why is it important to use an appropriate scale on a graph?
Deciding on a scale The scale of a graph is very important. It is determined by the data for each axis, and should be measured accordingly.
Why do we use charts and graphs?
A graph or a chart may be defined as a visual presentation of data. Businesses use graphs and charts to help them convey information and to make sense of data. Businesses have a wide variety of graphs and charts to choose from. They can use any of these charts and graphs.
What is the difference between a chart and a graph?
A graph is a diagram of a mathematical function, but can also be used (loosely) about a diagram of statistical data. A chart is a graphic representation of data, where a line chart is one form. So, a line chart could be called a graph or a plot, while a pie chart is neither a graph nor a plot.
How do you do statistical treatment?
In Data Analysis: Applying any statistical method like regression or calculating a mean to data. In Factor Analysis: Any combination of factor levels is called a treatment. In a Thesis or Experiment: A statistical treatment is a summary of the procedure, including statistical methods used.
What are the types of statistical treatment?
The two main types of statistical analysis and methodologies are descriptive and inferential. However, there are other types that also deal with many aspects of data including data collection, prediction, and planning.
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