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Presentation Of Statistical Data – Graphical Analysis
DOT DIAGRAMS IT IS THE PLACEMENT OF THE AVAILABLE PRICES IN A LINEAR SECTION * IT IS SUITABLE FOR A SMALL NUMBER OF OBSERVATIONS SOME OBSERVATIONS • THE AVERAGE CONSUMPTION PER GALLON OF GASOLINE IS VERY CLOSE FOR THE 3 CARS • THE VARIABILITY OF GASOLINE CONSUMPTION IN CAR 3 IS SMALLER TOO MANY VALUES…
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Political Ideologies 1: The concept of Ideology
Every political concept can be defined only within the intellectual, political and cultural conditions that prevail within which it acquires its primary, at least, meaning. For example, there is no single definition of freedom, the state or democracy as they are human inventions, which arose at some specific moment, in order to define an idea,…
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Presentation of Statistical Data 2
CONSTRUCTION OF FREQUENCY DISTRIBUTIONS – EXAMPLE: WEIGHT OF STUDENTS IN A FOURTH-GRADE 55, 51, 57, 63, 64, 55, 66, 70, 65, 62, 72.3, 51.5, 60.7, 52.3, 53.1, 54.7, 65.2, 62.7, 60.8, 55.2, 55.4, 57.7, 58.1, 60.4, 65. CLASS=6 (STURGESS TYPE=5.41022) CLASS WIDTH=3.6 The graph of a grouped distribution is made with the Histogram. FREQUENCY POLYGON…
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Hurst Exponent
Time series in statistics is a series of data points indexed in time order. Most commonly, these data points are considered at successive equally spaced points in time. Thus, we obtain then a sequence of discrete-time data. Examples of time series are daily measures of fever, yearly counts of an epidemic in a country, and the daily closing value of…
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Presentation of Statistical Data1
The most common way of presenting data is:FREQUENCY DISTRIBUTIONS AND HISTOGRAMS TERMINOLOGYFREQUENCY: The number of data in a class.RELATIVE FREQUENCY: The percentage of all data values that are in a class.HISTOGRAM: The graphical presentation of (relative) frequencies FREQUENCY DISTRIBUTION: CONSTRUCTION KEY POINTS IN CONSTRUCTING FREQUENCY DISTRIBUTIONS Note: Grouping data leads to loss of information. The…
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Data Types – Sources of Statistical Information – Research Types
DATA TYPES QUANTITATIVE: NUMERICAL OBSERVATIONS RESULTING FROM MEASUREMENT (e.g. Weight, Height, Age, Salaries, Stock Market Prices, Number of Products) QUALITATIVE: CATEGORIC OBSERVATIONS (NON-NUMERICAL) RESULTING FROM A SURVEY QUESTION (e.g. Gender (Male, Female), Marital Status (Married, Single), Type of Housing (Detached House, Apartment Building), Educational Level (First Degree, Second Degree, Third Degree) COMMENTS ON QUALITATIVE DATA:…
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Basic reason for using statistics – descriptive statistics
In many fields and many sciences, e.g. physics, biology, medicine, economics, etc., it is necessary to collect and analyze data concerning a set of objects in order to draw conclusions about it. Descriptive statistics: deals with the concise and effective presentation of the data of a statistical survey. (the other broad category is the inferential…
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Quantitative Data Analysis
Quantitative Data Analysis is a powerfull tool to offer solutions to real -world problems. There are numerous quantitative techniques (such as game theory, classical statistical techniques as time series, machine learning, quantitative methods of operational research etc.) and tools which can offer insights to real – world problems which arise. The focus of this page…
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What this blog is about
The progress of the technology can bring the quantitative approaches to a higher level and the mix of the technology with quantitative tools can help the community. The application areas of these tools include among others Economics, Politics, Computer Science, Information Technology, Healthcare, Finance, Electronics, and Communication Engineering. The scope is to offer insights to…
Quantitative Data Analysis
Quantitative data analyses for real-world problems.
Quantitative Data Analysis 