- •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
Analysis of research results
Among scientific researchers, empirical evidence (as distinct from empirical research) refers to objective evidence that appears the same regardless of the observer. For example, a thermometer will not display different temperatures for each individual who observes it. Temperature, as measured by an accurate, well calibrated thermometer, is empirical evidence. By contrast, non-empirical evidence is subjective, depending on the observer. Following the previous example, observer A might truthfully report that a room is warm, while observer B might truthfully report that the same room is cool, though both observe the same reading on the thermometer. The use of empirical evidence negates this effect of personal (i.e., subjective) experience.Ideally, empirical research yields empirical evidence, which can then be analyzed for statistical significance or reported in its raw form.
Analysis of datais a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.
Types of data:
Quantitative data is a number
Categorical data is one of several categories
Qualitative data is a pass/fail or the presence of a characteristic
The process of data analysis
Data analysis is a process, within which several phases can be distinguished:
1. Data cleaning
Data cleaning is an important procedure during which the data are inspected, and erroneous data are—if necessary, preferable, and possible—corrected. Data cleaning can be done during the stage of data entry. If this is done, it is important that no subjective decisions are made. The guiding principle is: during subsequent manipulations of the data, information should always be cumulatively retrievable. In other words, it should always be possible to undo any data set alterations. Therefore, it is important not to throw information away at any stage in the data cleaning phase. All information should be saved (i.e., when altering variables, both the original values and the new values should be kept, either in a duplicate dataset or under a different variable name), and all alterations to the data set should carefully and clearly documented, for instance in a syntax or a log.
2. Initial data analysis
The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that are aimed at answering the original research question. The initial data analysis phase is guided by the following questions:
Quality of data:
The quality of the data should be checked as early as possible. Data quality can be assessed in several ways, using different types of analyses.
Quality of measurements
The quality of the measurement instruments should only be checked during the initial data analysis phase when this is not the focus or research question of the study. One should check whether structure of measurement instruments corresponds to structure reported in the literature.
Characteristics of data sample
In any report or article, the structure of the sample must be accurately described. It is especially important to exactly determine the structure of the sample (and specifically the size of the subgroups) when subgroup analyses will be performed during the main analysis phase.
During the final stage, the findings of the initial data analysis are documented, and necessary, preferable, and possible corrective actions are taken.