- •Unit I
- •Improve your pronunciation:
- •Passive structures and their message
- •Ambiguous Ved forms
- •Vocabulary
- •Learn to use proper words
- •Study and research
- •V1. Translate into Russian:
- •V2. Translate into English:
- •V3. Read and translate Text 1 about scientific research in Supplementary reading. Pick up words and expressions which can be of use for you.
- •II. Рассмотрим перевод некоторых грамматических конструкций, содержащих ing-формы.
- •Pure and applied science
- •Automation in the research process
- •Ambiguous combinations of Ving and n
- •Vocabulary
- •Learn to use proper words
- •Experimental work
- •V1. Translate into Russian.
- •V2 Translate into English.
- •V3. Read and translate Text 2 about empirical research in Supplementary Reading. Pick up the words and expressions which might be of use for you.
- •Improve your pronunciation:
- •The infinitive
- •Инфинитивные обороты
- •Vocabulary
- •Learn to use proper words
- •Showing and proving
- •V1. Translate into Russian:
- •V2. Translate the words in brackets. Then translate the sentences into Russian:
- •V3. Translate into English:
- •V4. Read and translate Text 3 about evaluation of research results in Supplementary reading. Pick up the words and expressions which might be of use for you.
- •V5 Write a piece of 5-7 sentences to characterize the process of evaluating the data that you have obtained in the course of your research. Use grammar structures and vocabulary studied. Unit 4
- •Improve your pronunciation:
- •Modal verbs and their equivalents
- •Summary chart of modals and similar expressions
- •Vocabulary
- •Learn to use proper words
- •Obtaining and analysing results
- •V1. Translate into English:
- •V2. Read and translate text 4 about analysis of research results in Supplementary Reading. Pick up the words and expressions which might be of use for you.
- •Conditionals without if
- •Sentences with as if, as though
- •Object clauses with subjunctive
- •Vocabulary
- •Learn to use proper words
- •Describing trends and tendencies
- •V1. There are a lot of verbs and nouns describing changes in size, number, price, value etc. Find the verbs that indicate an upward, downward or horizontal movement:
- •V2. Describe the rate and size of change observed:
- •V3. Complete the sentences with the prepositions: of, per, at, by, from…to.
- •V4. Translate into Russian:
- •V5. Read the example of a scatter graph description. Pick up words and expressions which might be of use for you.
- •V6. Write 5-7 sentences describing some trends in the field of your research. Unit 6
- •Improve your pronunciation:
- •Word building
- •Suffixes of the noun
- •The noun
- •2. Множественное число некоторых заимствованных из других языков существительных образуется по правилам этих языков:
- •3.Существительное в роли определителя: правило ряда
- •Vocabulary
- •Learn to use proper words
- •Comparing and contrasting
- •V1. Translate into Russian:
- •V2. Translate into English:
- •V3. Read and translate text 5 where fundamental science and experimental science are compared. Pick up the words and expressions which might be of use for you.
- •V4. Write an essay of 5-7 sentences comparing :
- •Improve your pronunciation:
- •Word building
- •Grammar слова-заместители
- •3) This, these:
- •Vocabulary
- •Emphasizing
- •Concluding
- •V1. Translate into Russian.
- •V2. Write an essay about your research work using all grammar structures and vocabulary studied. Unit 8
- •Improve your pronunciation:
- •Prepositions and conjunctions
- •Наиболее употребительные составные предлоги:
- •Наиболее употребительные составные союзы
- •Cлова, на которые следует обратить особое внимание
- •Vocabulary
- •Learn to use proper words
- •V1. Translate the sentences
- •V2. Make up a story about a scientist using idioms and expressions with the word “time”. You might start as follows:
- •To make and to do
- •V3. Complete the sentences with to make or to do in the proper form. Then translate them into Russian.
- •V4. Translate the sentences
- •V5. Continue the story about the scientist but this time try to use the verbs “to make” and “to do”. Unit 9 word building
- •Complex sentence
- •Vocabulary learn to deduce the meaning of english words:
- •Supplementary reading
- •Research
- •Empirical research
- •Evaluation and improvement
- •Aspects of validation
- •Analysis of research results
- •The process of data analysis
- •1. Data cleaning
- •2. Initial data analysis
- •3. Main data analysis
- •Fundamental science and applied science compared
- •Supplementary information most widespread abbreviations
- •Linking words and phrases
- •Table of mathematical symbols
- •Main sources of information
Aspects of validation
The most tested attributes in validation tasks may include, but are not limited to
Accuracy
In the fields of science, engineering, industry and statistics, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to its actual (true) value. The precision of a measurement system, also called reproducibility or repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. Although the two words can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method.
Accuracy indicates proximity of measurement results to the true value, precision to the repeatability or reproducibility of the measurement
A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. Eliminating the systematic error improves accuracy but does not change precision.
A measurement system is called valid if it is both accurate and precise. Related terms are bias (non-random or directed effects caused by a factor or factors unrelated by the independent variable) and error (random variability), respectively.
The terminology is also applied to indirect measurements, that is, values obtained by a computational procedure from observed data.
In addition to accuracy and precision, measurements may have also a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement.
Repeatability or test-retest reliabilityis the variation in measurements taken by a single person or instrument on the same item and under the same conditions. A measurement may be said to be repeatable when this variation is smaller than some agreed limit. According to the Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, repeatability conditions include:
the same measurement procedure
the same observer
the same measuring instrument, used under the same conditions
the same location
repetition over a short period of time.
Reproducibility is one of the main principles of the scientific method, and refers to the ability of a test or experiment to be accurately reproduced, or replicated, by someone else working independently.
The results of an experiment performed by a particular researcher or group of researchers are generally evaluated by other independent researchers who repeat the same experiment themselves, based on the original experimental description (see independent review). Then they see if their experiment gives similar results to those reported by the original group. The result values are said to be commensurate if they are obtained (in distinct experimental trials) according to the same reproducible experimental description and procedure.
Reproducibility is different from repeatability, which measures the success rate in successive experiments, possibly conducted by the same experimenters. Reproducibility relates to the agreement of test results with different operators, test apparatus, and laboratory locations. It is often reported as a standard deviation.
While repeatability of scientific experiments is desirable, it is not considered necessary to establish the scientific validity of a theory. For example, the cloning of animals is difficult to repeat, but has been reproduced by various teams working independently, and is a well established research domain. One failed cloning does not mean that the theory is wrong or unscientific.
Limit of detection ; Limit of quantification
In analytical chemistry, the detection limit, lower limit of detection, or LOD (limit of detection), is the lowest quantity of a substance that can be distinguished from the absence of that substance (a blank value) within a stated confidence limit (generally 1%). The detection limit is estimated from the mean of the blank, the standard deviation of the blank and some confidence factor. Another consideration that affects the detection limit is the accuracy of the model used to predict concentration from the raw analytical signal.
There are a number of different "detection limits" that are commonly used. These include the instrument detection limit (IDL), the method detection limit (MDL), the practical quantification limit (PQL), and the limit of quantification (LOQ). Even when the same terminology is used, there can be differences in the LOD according to nuances of what definition is used and what type of noise contributes to the measurement and calibration.
Curve fittingis the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints. Curve fitting can involve either interpolation, where an exact fit to the data is required, or smoothing, in which a "smooth" function is constructed that approximately fits the data. A related topic is regression analysis, which focuses more on questions of statistical inference such as how much uncertainty is present in a curve that is fit to data observed with random errors. Fitted curves can be used as an aid for data visualization, to infer values of a function where no data are available, and to summarize the relationships among two or more variables. Extrapolation refers to the use of a fitted curve beyond the range of the observed data, and is subject to a greater degree of uncertainty since it may reflect the method used to construct the curve as much as it reflects the observed data.
Text 4