SZL 2111: HIV/AIDs - Full Notes
| Institution | JKUAT |
| Course | Common Units |
| Year | 1st Year |
| Semester | Unknown |
| Posted By | Jeff Odhiambo |
| File Type | |
| Pages | 153 Pages |
| File Size | 934.29 KB |
| Views | 8005 |
| Downloads | 0 |
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Description
General introduction: Public health and hygiene, human reproductive system, sex and sexuality. History of sexually transmitted diseases (STDs); History of Human Immunode ciency virus/ Acquired Immune deficiency Syndrome(HIV/AIDS), Comparative information on trends, global and local distribution, Justification of importance of course. Biology of HIV/AIDS; Overview of immune system, natural immunity to HIV/AIDS. The AIDS virus and its life cycle, disease progression, transmission and diagnosis.
Discordant couples. Treatment and Management; nutrition, prevention and control; Abstain, Be faithful, Condom use, Destigmatize HIV/AIDS (ABCD) methods and an-tiretroviral drugs and vaccines. Pregnancy and AIDS. Management of HIV/AIDS patients. Social and cultural practices: Religion and AIDS. Social stigma on HIV/AIDS. Behavioral change. Voluntary Counseling and Testing Services. Gender and HIV/AIDS. Drug and alcohol abuse and HIV/AIDS. Poverty and AIDS. Families and AIDS orphans. Government policies: Global policies of AIDS. Legal rights of AIDS patients. AIDS Impact: Family /society setup, population, agriculture, education, health, industry, development, economy and other sectors.
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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.
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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.
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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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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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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.
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