Abstract:

“Types of charts and their uses” There are different types of charts used in statistics science, in order to facilitate the presentation of statistical results. Those types are Bar chart, Histogram (frequency distribution diagram), The frequently polygon, Frequently curve, Line graph, Pie diagram. In this research each type of them had been identified their main idea specifically, and show each type purpose and use, to implement in different categories and fields. Keywords: Graphic presentation of data, Statistical charts and their uses, Modern methods to Present statistical data, Graphical methods to present statistical data.

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1

Introduction

Mathematical statics is a primarily concerned with the study of the basic principles of arithmetic, elementary, and certain advanced topics of classical algebra, geometry and trigonometry. Statics data results are difficult to present by using long rows, it is difficult to get information and difficult to analyze those data. So, there are numerous chart types for data presentation in order to summarize data and that will lead to facilitate how to deal with these kinds of data without loss any of data quantity. And that will reduce time and effort consuming So they are the most attractive and effective presentation of data.

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Graphic presentation of data

Graphs represent pictorial representation of the distribution of data. Graphs should Present a clear and accurate picture about the date and convey an easy-to-understand Message .Graphs include labels with units of measurements ,a title that accurately Describes the content of the graph ,and a scale on each axis that neither distorts nor Exaggerates the date .Sample size should be on the graph or legend . The type of graph used to present the data depends on the type of data and the design of the experiment. The following are the methods used to present statistical data.

• Bar chart.

• Histogram (frequency distribution diagram).

• The frequently polygon.

• Frequently curve.

• Line graph.

• Pie diagram.

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Bar Chart

Bar charts have a separate domain of categories, and are usually scaled in order that each one the information can fit on the chart. once there's no natural ordering of the classes being compared, bars on the chart is in addition organized in any order. Bar charts organized from highest to lowest incidence are expressed as pareto charts. Bar graphs/charts offer a visible presentation of categorical information. Categorical data could be a grouping of knowledge into separate teams, such as months of the year, age group, shoe sizes, and animals. These classes are typically qualitative. during a column bar graph, the classes seem on the horizontal axis; the peak of the bar corresponds to the worth of every class. The bars may be drawn with their standard errors (S.E) as well as the sign of significance When it is compared to the value of a reference standard or a control. Used to show a distribution of data points or perform a comparison of metric values across different subgroups of data.

Bar chart can be classified into two main types:

A). Simple bar chart

This type of graph is used when one phenomenon is measured and it is important that the Base line begins at the zero otherwise false visual impressions are created. A break in the Y-axis.

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B). Multiple Bar Chart

This type of graph is used to show more than one set data by grouping bars together. The Distance between each group of bars should be suitable and equal and the same distance is left between the first bar and the Y-axis.

The bars should be identified by shading, coloring or stippling.

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Histogram (frequently distribution diagram):

A bar graph may be a chart that groups numeric information into bins, displaying the bins as divided columns. They're used to depict the distribution of a dataset: how often values fall into ranges, represent of the distribution of numerical or categorical data. Its width represents class intervals and whose areas are proportional to the corresponding frequencies of the particular data values within each interval (as area = length * width). The best graphic presentation foe continuous variate is the histogram. Histogram with 'Frequency' on the y-axis and 'Age' on the x-axis

36 25 38 46 55 68 72 55 36 38

67 45 22 48 91 46 52 61 58 55

Histogram used to estimate density function of rainfall and river discharge data, analyzed with a probability distribution, are used to gain insight in their behavior and frequency of occurrence.

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The Frequency polygon

A frequency two-dimensional figure may be a graph created by using lines to join the midpoints of every interval, or bin. The frequencies are represented by the heights of the points. A frequency two-dimensional figure is often created from the bar graph or by calculating the midpoints of the bins from the statistical distribution table. The center of a bin is calculated by adding the higher and lower boundary values of the bin and dividing the add by two. Used to provide us with an understanding of the shape of the data and its trends.

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Frequency curve

A frequency-curve is a simple curve that the total space is taken to be unity. it's a limiting style of a histogram or frequency plane figure. The frequency-curve for a distribution are obtained through drawing a smooth and free hand curve through the mid-points of the upper aspects of the rectangles forming the histogram.

Types of frequently distribution curve

1. Normal or symmetric frequency distribution curve (Gaussian

distribution).

When the frequency curve can be divided into two equal parts by a line passing through the center of the distribution – symmetric.

Features of the normal distribution curve

• The curve is bell -shaped (or may U-shaped) and symmetrical.

• It has only one modal value (unimodal) coinciding with the peak and dividing the area under the curve into two equal halves.

• The highest frequency in the middle of the curve.

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• The curve approaches, but never meets, the abscissa at both high and low ends (The curve is asymptotic at the base).

• The mean. median and mode are all equal dividing the curve into two equals halves.

2. Skewed or Asymmetric frequency curve.

When the frequently curve extends in one direction than the other – asymmetric

Skewed curve types.

• A left-skewed distribution has a long-left tail. Left-skewed distributions also are referred to as negatively-skewed distributions. That’s as a result of there's an extended tail within the negative direction on the amount line. The mean is additionally to the left of the height.

• A right-skewed distribution has a long right tail. Right-skewed distributions also are referred to as positive-skew distributions. That’s as a result of there's an extended tail within the positive direction on the amount line.

The mean is additionally to the correct of the height.

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• Bimodal frequency distribution curve.

Two peaks of data, which usually indicates that there are two different groups. Two peaks could also indicate that those data are sinusoidal.

Asymmetric frequency distribution curve applications:

• Skewness could be a descriptive statistic which will be used in conjunction with the histogram and therefore the normal quantile plot to characterize the info or distribution.

• Skewness indicates the direction and relative magnitude of a distribution's deviation from the traditional distribution.

• With pronounced skewness, standard statistical inference procedures like a confidence interval for a mean will be not only incorrect, within the sense that actuality coverage level can differ from the nominal (e.g., 95%) level, however they'll also lead to unequal error chances on both sides.

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• Skewness could also be wont to get approximate possibilities and quantiles of distributions (such as worth at risk in finance) via the Cornish-Fisher growth.

• Several models assume normal distribution; i.e., knowledge is symmetrical relating to the mean. the standard distribution includes a skewness of zero. but primarily, data points won't be perfectly symmetric. So, associate understanding of the skewness of the dataset indicates whether or not deviations from the mean are attending to be positive or negative.

Line graph

Used to visualize the value of something over time. For example, in case of dose - response curves and when the effect is measured at different times. The line graph can be divided into the following classes depending on the paper on which

the graph is drawn:

a). Arithmetical or natural scale graph.

The graph is drawn on paper. If 2 or more curves are drawn on the paper, different types of lines such as solid, long dashes ,and short dashes are used . The arithmetic scale graph is sigmoid or formed and can't be used for comparison results in bioassays and then a change of the information into other units is carried out.

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Uses and applications in medicine

• modeling of growth of tumors.

• modeling of a pandemic.

b). Log -Log scale graph .

Is a two-dimensional graph of numerical knowledge that uses index scales on each the Y- axis and x-axis. the most advantage of that style of scale is that wide selection of values are often premeditated than once using arithmetic paper. Also, the lines become straight and this is important in the bioassay when comparing the effect of a test preparation with a standard.

c). Log-probit scale graph :

This type of graph the log dose is plotted on the X-axis against the probit of the response which is plotted on the Y-axis .Usually the response and the experiment usually the response is in the form of percentage response and the experiment usually follows an all or non-response .There is a table which transform the percentage response to the corresponding probit .

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Uses and Applications:

This type of scale used in probit analyses. A method of analyzing the relationship between a stimulus (dose) and the quantal. Used to analyze several types of dose-response or binomial response experiments In a form of fields. normally employed in toxicology to work out the relative toxicity of chemicals to living organisms.

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Pie Diagram

Chart (or a circle chart) could be a circular applied mathematics graphic, that is split into slices for instance numerical proportion. every slice is proportional to the amount it represents. Best pie diagram doesn’t have any over 5 to 6 sectors. Generally used to show percentage or proportional data and usually the percentage represented by each category is provided next to the corresponding slice of pie.

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Conclusion

To conclude using Graphic Presentation of Data different types one of the most Effective method to make statistical data easier to deal with, and more practical to present it, that will lead to more effective analysis data outcomes. Using Bar chart type is a method to combine different types of data in one chart and separate them to different classes and organized them from highest to lowest. Histogram Chart used with groups of numeric information and arrange them into bins, and it considered as best graphic presentation foe continuous variate is the Histogram. The Frequency polygon it is a chart which is so close to Histogram chart principle, different by draw a line that combine all bins tips with each other, which will present the shape of data and its trends.

Frequency curve it is a simple curve that has a combination with its principle with the Histogram and The Frequently polygon, It is a simple hand free curve with a mid-point at the highest limit of the curve .It has different types differ from each other according to the position of the mid-point (curve climax) , Normal type that can be divided in to two equal halves , Asymmetric type which divided into two types left (negative skewness)one which mean its additionally to the left of the height, and the right(positive skewness) one which means additionally to the correct of the height, and Bimodal frequency distribution curve, two peaks of data, which usually indicates that there are two different groups. Line Graph used to observe something(variable) over time, it has 3 main types Arithmetical or natural scale graph, Log -Log scale graph, Log- probit scale graph. Pie Chart circular applied mathematics chart, used to show percentage of data and as a slice limit on that circle.