# ICT 119-Elementary Statistics - PowerPoint PPT Presentation

ICT 119-Elementary Statistics

1 / 26
ICT 119-Elementary Statistics

## ICT 119-Elementary Statistics

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
##### Presentation Transcript

1. ICT 119-Elementary Statistics For all B.SC.ICT-B & B.SC.ITS Students By: Masoud AmriKomunte Department of mathematics and Statistics Studies (MSS) MzumbeUniversity Office: Block B 209 Mobile: 0713227333 Email: makomunte@mzumbe.ac.tz

2. Introduction to Statistics • The systematic and scientific treatment of quantitative measurement is precisely known as statistics. • Statistics may be called as science of counting. • Statistics is concerned with the collection, classification (or organization), presentation and analysis of data which are measurable in numerical terms.

3. Statistical Investigation What is a statistical investigation ?

4. statistical investigation What is a statistical investigation ? The gathering of data and analysing information to help people make decisions when faced with uncertainty

5. Stages of Statistical Investigation Define the objectives Collection of Data Organization of data Presentation of data Analysis of data Interpretation of Results

6. Planning For An Investigation • At the planning stage you have to consider all the stages involved right from the first stage to the last stage. • The most important stage of all is to clearly define the objectives of the investigation. • After defining the objectives of the investigation then make sure that only data relevant to the objectives are collected.

7. Types Of Statistical Investigation There are two types:- • General purpose statistical investigation. In this type the objective is to address a number of problems in just one investigation these problems may be social, economic, political etc. • Specific purpose statistical investigation. In this type we try to collect information relevant to a specific purpose.

8. It is divided into two major parts: Descriptive and Inferential Statistics. Descriptive statistics, is a set of methods to describe data that we have collected. i.e. summarization of data. Inferential statistics, is a set of methods used to make a generalization, estimate, prediction or decision. When we want to draw conclusions about a distribution. Division of Statistics

9. Collection of Data • Data can be collected by two ways: >>> Primary Data Collection It is the data collected by a particular person or organization for his own use. >>> Secondary Data Collection It is the data collected by some other person or organization, but the investigator also get it for his use.

10. Methods of Primary data collection • Direct personal interview • Data through questionnaire • Indirect investigation Etc.

11. Methods of Secondary data collection • Data collected through newspapers & periodicals. • Data collected from research papers. • Data collected from government officials. • Data collected from various NGO, UN, UNESCO, WHO, ILO, UNICEF etc. • Other published resources

12. Questionnaire A questionnaire is a form in hard/soft copy which asks for certain information and spaces are provided for recording responses. • A questionnaire may be self-administered or may be administered by an interviewer. • A self-administered questionnaire may be sent by mail or may be delivered in personal.

13. Mail Questionnaire • Practicable because it is cheaper to collect the information as there are no interviewer involved. • Also practicable when a vast area with very many respondents is to be covered.

14. Limitations Of Mail Questionnaire • Need a literate population. That is the respondents should be able to read the questions and fill in the required responses. • Need an efficient postal/internet system.

15. Questionnaire Design The guiding rules for questionnaire design are basically:- • Appearance The questionnaire need to be attractive especially if it is a mail questionnaire. • Length of the questionnaire As far as possible a questionnaire should be short. A very long questionnaire will tend to discourage a respondent, especially if it is a mail questionnaire.

16. Questionnaire Design The guiding rules • Wording -Simple, clear and precise questions. Avoid ambiguous questions. The respondents should be able to interpret a question in one and only one way. A question like “how big is your house?” has an element of ambiguity, some respondents may interpret the question in term of dimension and yet others in terms of number of rooms. -Questions should be presented in a logical order. If there is a known or established order of things then that order should be followed.

17. Questionnaire Design The guiding rules • Wording -Avoid very personal or sensitive questions. -Avoid leading quetions. -Start with the simplest questions and continue according to the complexity of the issues.

18. Classification of data • Classification is a process of arranging data into sequences and groups according to their common characteristics or separating them into different but related parts. • It is a process of arranging data into various homogeneous classes and subclasses according to some common characteristics.

19. Scrutiny of data • Collected data should be checked carefully before they are subjected to any statistical treatment. For however useful statistical method may be when properly applied, then can not give reliable information from faulty and unreliable data. • In some cases the errors may be obvious for example impossible values in measurements. If you can see a figure of say 200 kilograms for a weight of a school child then that is clearly impossible.

20. Scrutiny of data • In some cases number might not be impossible but may seem very unlikely. If for example it is recorded that a household of 2 people it consumes 5kgs of rice a day, this should rouse suspicion.

21. Presentation of Data • Data should be presented in such a manner, so that it may be easily understood and grasped, and the conclusion may be drawn promptly from the data presented. e.g. >>> Histogram >>> Frequency polygon & curve >>> Pie Chart >>> Ogives >>> Bar Chart >>> etc

22. Variables • Discrete Variable e.g. Number of books, table, chairs • Continuous Variable e.g. Height, Weight • Quantitative Variable That can be measured on a scale, that is, it can be expressed as number • Qualitative Variable That can not be measured on a scale, that is, it can not be expressed as number but they can be put in categories.

23. Example Solution Suppose you survey potential voters among the people on main street during lunch to determine their political affiliation and age, as well as their opinion on the ballot measure. Classify the variables as quantitative or qualitative. Political affiliation is a qualitative variable (categories). Age is a quantitative variable (numbers). Opinion on the ballot measure is a qualitative variable (categories).

24. Statistics functions & Uses • It simplifies complex data • It provides techniques for comparison • It studies relationship • It helps in formulating policies • It helps in forecasting • It is helpful for investigation purpose • A quickest way in decision making since Statistical methods merges with speed of computer through SPSS, STATA, MATLAB, MINITAB etc.

25. Scope of Statistics • In Business Decision Making • In Medical Sciences • In Actuarial Science • In Economic Planning • In Agricultural Sciences • In Banking & Insurance • In Politics & Social Science

26. Distrust & Misuse of Statistics According to Aaron Levenstein: “Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.” • Statistics is like a clay of which one can make a God or Devil. • Statisticians are the liars of first order. • Statistics can prove or disprove anything.