CIS 403: SOCIAL COMPUTING AND INFORMATICS
| Institution | UNIVERSITY OF NAIROBI |
| Course | BACHELOR OF INFORMAT... |
| Year | 4th Year |
| Semester | Unknown |
| Posted By | stephen oyake rabilo |
| File Type | |
| Pages | 10 Pages |
| File Size | 399.12 KB |
| Views | 6987 |
| Downloads | 0 |
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Description
Social computing and informatics brings together people, technology, information and innovation. People, organizations, industries and communities interact, connect and collaborate in social context. Digital systems support online research, education, health, communication and entertainment. Organizations harness the power of social computing and informatics to enhance business transactions and boost reputation. Amazon applies social computing to engage and captivate customers, boasting impressive 27.8 million Facebook page likes and 2.7 million followers. Amazon promptly and directly responds to the customers on Facebook, swiftly addressing all comments and ensuring that clients are well satisfied with the services. Due to comprehensive collection of feedback and reviews from the previous customers, effectively demonstrating the excellence of its products and services, most people trust Amazon. Hence, without digital systems and connections to the Internet nothing can be achieved. Bachelor of Information Science (BIS) level four or fourth year consists of 10 core course units or subjects, with 5 course units per semester. BIS CIS 403: Social Computing and Informatics explores human-computer/human-machine/human-machine product interactions and its impact in the society.
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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
8535 Views
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152.45 KB
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
8490 Views
11 Downloads
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
6475 Views
6 Downloads
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
7391 Views
1 Downloads
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
5805 Views
1 Downloads
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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