Nanoscience, Nanotechnology, and Chemistry
| Institution | UNIVERSITY |
| Course | BACHELOR OF SCIENCE... |
| Year | 4th Year |
| Semester | Unknown |
| Posted By | stephen oyake rabilo |
| File Type | |
| Pages | 8 Pages |
| File Size | 556 KB |
| Views | 7354 |
| Downloads | 1 |
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Description
Nanoscience is the emerging science of objects that
are intermediate in size between the largest molecules and
the smallest structures that can be fabricated by current
photolithography; that is, the science of objects with smallest dimensions ranging from a few nanometers to less than
100 nanometers.[1–3] In chemistry, this range of sizes has historically been associated with colloids, micelles, polymer
molecules, phase-separated regions in block copolymers,
and similar structures—typically, very large molecules, or
aggregates of many molecules. More recently, structures
such as buckytubes, silicon nanorods, and compound semi conductor quantum dots have emerged as particularly interesting classes of nanostructures. In physics and electrical engineering, nanoscience is most often associated with quantum behavior, and the behavior of electrons and photons in
nanoscale structures. Biology and biochemistry also have a
deep interest in nanostructures as components of the cell;
many of the most interesting structures in biology—from
DNA and viruses to subcellular organelles and gap junctions—can be considered as nanostructures.
Below is the document preview.
LESSON 4: MEASURES OF DISPERSION
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The measures of central tendency are not sufficient measures to reveal the shape of the distribution of data set. The measures that show the spread of a data set are called the measures of dispersion. The main measures of dispersion are range, inter quartile range, standard deviation, variance and coefficient of variation. In this lesson we will discuss these measures of dispersion.
9 Pages
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LESSON 1: DEFINITION OF STATISTICS, DATA COLLECTION AND DATA PRESENTATION TECHNIQUES
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Statistics is the science of data. This involves collecting, classifying, summarizing,
organizing, analyzing, and interpreting numerical information.
7 Pages
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LESSON 2: MEASURES OF CENTRAL TENDENCY
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One of main objectives of statistical analysis is to obtain one single value that describes the characteristic of the entire mass of unwieldy data. Such a value is called the central value or average value. In this lesson we will consider some of central values which are commonly used.
8 Pages
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LESSON 3: MEASURES OF CENTRAL TENDENCY cont..
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In this lesson we will discuss the other measures of location or measures of central tendency namely, geometric mean, harmonic mean, median and mode of given data.
10 Pages
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246.31 KB
THEORIES OF LANGUAGE ACQUISITION
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Over the last fifty years, several theories have been put forward to explain the process by which children learn to understand and speak a language. They can be summarised as follows:
4 Pages
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SZL 105: LABORATORY METHODS AND TECHNIQUES IN ZOOLOGY
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A laboratory is a closed or isolated environment where scientific experiments and procedures are carried out. Laboratory studies are applied in all areas of science namely. Physics, chemistry,biology, agriculture, health, environment, geology, mining among others.
31 Pages
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681.05 KB
SST 305: Theory of Estimation Notes
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The objective of statistics is to make an inference about a population based on information contained in a sample. Most statistical inference procedures involve either estimation or hypothesis testing. This course looks at estimation.
41 Pages
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3.41 MB
SMA 335: Ordinary Differential Equation 1
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The subject of differential equations constitutes a very important and useful branch of
modern m mathematics. In this lesson we sh all consider some definition of ordinary
differential equations.
156 Pages
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2.32 MB
LESSON 7: REGRESSION AND CORRELATION ANALYSIS
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In this lesson we will discuss regression and correlation. Correlation analysis deals with the association between two or more variables; while regression analysis attempts to establish the nature of the relationship between variables.
11 Pages
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271.03 KB
LESSON 6: SKEWNESS AND KURTOSIS
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Skewness refers to lack of symmetry. A skewed distribution is a frequency distribution that is asymmetric (not symmetric). When the longer tail of a distribution extends to the right, it is said to be skewed to the right and when the longer tail of a distribution extends to the left, it said to be skewed to the left.
9 Pages
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