Tag Archives: Math

Importance of Statistical and Experimental Design


Importance of Statistical and Experimental Design

Every operation in a system requires careful planning and every experiment that yields a result requires verification and validation. Statistical and Experimental design by CAMO Software is based around this concept, to assist other companies and research centers in their experimentation, throughout the world. It deals with the design of experiments containing variables, under the full control of technical experts and designers who are responsible for many tasks such as A/B testing, split testing, multivariate data analysis and graphic design.

Role of CAMO software in Experimental Design

CAMO Software and tools related to experimentation are designed with all major types of manufacturing businesses in mind, such as food and beverages, software and hardware, pharmaceuticals, mining, paper and plastic industries. Planned experimentation is a part of chemical formulations, components, elements, materials and physical objects. The company, through its statistical analysis and experimental design, offers multiple data screening and evaluation, product management support, integration of technology into productivity, and assessment of economic returns. The services thus offered are meant for long-term use of requirements involving various elements with varying objectives. The fluctuating nature of expectations demand for caution during the design. For example, if the project undertaken with CAMO Software is based on agriculture and farming, the trials include :

– Assessment of land availability

– Determine the soil heterogeneity and guidance for modification of its characteristics

– Determine the effect of change in soil fertility on the land

– Ensure combined analysis and maintain consistency in the design

– Reduce or eliminate unnecessary previous factors during the experiment

– Integrate farmers’ trials to the experiment wherever necessary

– Determine the size of farming plot with possibility of errors taken into consideration

Important Experimentation Steps

Following are the seven major tips that are crucial in any experimentation in order to find a solution to a given problem:

– Define the problem and ready the variable

– Define objectives and check with the hypothesis

– Test the hypothesis including the stated variable

– Collect the data

– Analyze the data

– Interpret the target result

– Conclude the hypothesis.

CAMO Software engages in statistical methods to ensure proper execution of the above seven steps in the assigned experiment. The steps also touch on crucial areas of data such as samples collection, screening, coding, transformation, variables, parameters and analysis.

Collection, Screening and Analysis of Data in Detail

It’s a common idea that every data collected in an experiment becomes the part of that experiment in question. This is not true because some data do not adequately represent the matter under study. For example, a faulty sampling technique may ruin the whole observation or an incorrect calculation, a faulty measuring apparatus may wrong the data. Efficient data collection and screening involves weeding out such faulty data. The screening procedure approach makes sure that the data is rechecked, which may involve re-examining the collected data or revisiting the site when there is a doubt. A good successful practice means re-computing the extracted values and ensuring consistency throughout the process.

Another professional way to determine the appropriate value of a data is through drawing a relation between the input data and statistically acceptable data. This screening process, also known as spurious observation, depends on statistical distribution theory. It is based on classifying the data where maximum confidence lies. If the outlier falls outside this limit, the suspected data is rejected.

James is passionate about Experimental Design, he works as a data analyst for Camo.



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Statistics and IT Go Together Like Movies and Popcorn

Certain things in life are made for each other: cheese and tomato, movies and popcorn, rainy days and hot chocolate, and … statistics and IT. Imagine being a statistician with no computer programmes or fancy software to help you organise and make sense of all the data around you. Imagine being surrounded by reams of paper and having to create graphs and charts by hand. Oh yes, IT is a boon to statistical analysis.

Statistics combines scientific and mathematical principles to collect, analyse and interpret data. They also devise data collection methods to ensure that the information is collected in a quantifiable manner. If you’re not highly focused and don’t possess Vulcan-like logic then you should probably consider another career.

Becoming a statistician

It should go without saying that you need to have taken maths and science throughout your school career. Statistics is not a field that you spontaneously leap into after years of home economics, history and geography, but if you’re the kind of person prone to spur of the moment gut decisions then, once again, statistics might not be for you.

So, you need maths and science – with good grades – and then degree. Not just any old degree will do. A bachelor’s degree in maths or science is a good starting point, but then you need to up the stakes and get your master’s degree and, if you can, a PhD. Statistics is one of those fields where a PhD will stand you in good stead, rather than simply being an interesting way to occupy five years of your life.

Your degree programme should incorporate maths (particularly calculus and linear algebra, according to and statistics (of course), computer science, probability, logic and even psychology. You’ll also need to fully understand all forms of research methodology and be able to define terms such as Chi-squared test, analysis of variance, mean square weighted deviation, and Pearson product-moment correlation coefficient.

It’s important to note that just because you’re going to be neck deep in numbers doesn’t mean you can’t combine your statistical skills with other subjects. Statisticians are required in a wide range of fields, including biology (biostatistics), economics (econometrics), geography (geostatistics), business (business analytics), psychology (psychometrics), health (epidemiology) and reliability engineering – Wikipedia.

One of the reasons why IT is so important to statisticians is that they rely heavily on software that helps them arrange, access and assimilate information. Software can draw on numbers and run complicated calculations based on even more complicated formulas to generate charts, graphs and tables that help statisticians analyse data and reach logical conclusions. These programmes also detect minor errors that might otherwise have been missed.

Some statisticians also find that they have to tweak existing software or write their own programmes so they can run the tests and formulas they require.

IT is a boon to statistical analysis indeed.

Sandy Cosser writes on behalf of Now Learning, which promotes online IT courses and an assortment of other degree programmes in Australia.


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Five Essential Skills for a Technology Career

A Career in technology can be interesting, challenging, and lucrative. If you are looking at a career in technology, whether information technology (IT) or something more “blue collar” like industrial engineering, these five essential skills will help you succeed.


Technology careers draw heavily on math. Students should have a good grasp of the various branches of mathematics such as algebra, trigonometry, geometry, and calculus. Whether you will actually use these specific skills every day is unimportant. Understanding math helps you understand essential technology concepts. A computer may do the math for you, but you need to understand it, especially if you are programming the computer to do that math.

Advanced knowledge of mathematics can also help advance your future career. If you want to go from being an IT professional working on the customer side of things to getting involved in the design end, it will be easier if you can speak intelligently about mathematics.

Basic Physics

Most technology fields require at least a cursory knowledge of physics. Your need for deep understanding will depend on the career you choose. Researchers are running advanced simulations to try to understand how the universe was formed. If you don’t understand physics, you’ll have a hard time breaking into this exciting field of study.

Problem Solving

Problems solving is at the heart of information technology. IT workers solve problems every day, all day. They find solutions through hands-on help, guidance, programming new software, inventing new technologies and more.

Learning to approach problems effectively is vital to success in this area. If you can analyze what needs to be done, use creative techniques to find a solution and figure out how to implement it, you have a great head start in a technology career.

Systems Analysis

An analytical mind can look at a problem and logically trace it back to its roots. This skill is especially important for programmers and debuggers. Systems must be broken down into their component parts and dealt with in a specific yet integrated way. Dealing with systems and integrating your insights on the problem can be very helpful in solving technological problems of all sorts.

Communication Skills

Finally, good communication skills are a necessity in this field. Luckily, even poor communicators can improve, especially since most messages will go via email. Students must be able to explain problems and solutions clearly, communicate effectively and make themselves understood while maintaining pleasant and constructive exchanges of information. These skills are not technical ones per se, but they should not be overlooked as part of a technology professional’s core skill set. They are vital to information exchange that is effective, efficient, and cooperative.

Jessica Bosari writes about technology careers for Students can find information about many technology jobs, such as computer forensics careers.


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