Basic StatisticsHistory, Introduction, Basic Terms

Predicting Disease 85 to 95 percent of lung cancers are smoking related. The statistic should tell you that almost all lung cancers are related to smoking and that if you want to have a good chance of avoiding lung cancer, you shouldn't smoke. Weather forecasts These computer models are built using

statistics that compare prior weather conditions with current weather to predict future weather.

Medical Studies Scientists must show a statistically valid rate of effectiveness before any drug can be prescribed. Statistics are behind every medical study you hear about.

 Quality Testing Companies make thousands of products every day and each company must make sure that a good quality item is sold. But a company can't test each and every item that they ship to you, the consumer. So the company uses statistics to test just a few, called a sample, of what they make. If the sample passes quality tests, then the company assumes that all the items made in the group, called a batch, are good.   Stock Market Another topic that you hear a lot about in the news is the stock market. Stock analysts also use statistical computer models to forecast what is happening in the economy

Why Statistics?

The purpose of statistics is to develop and apply methodology for extracting useful knowledge from both experiments and data. In addition to its fundamental role in data analysis, statistical reasoning is also extremely useful in data collection (design of experiments and surveys) and also in guiding proper scientific inference (Fisher, 1990).

Statistics is neither really a science nor a branch of mathematics. It is perhaps best considered as a meta-science (or meta-language) for dealing with data collection, analysis, and interpretation. As such its scope is enormous and it provides much guiding insight in many branches of science, business

History

The Word statistics have been derived from Latin word “Status” or the Italian word “Statista”, meaning of these words is “Political State” or a Government.

Shakespeare used a word Statist is his drama Hamlet (1602). In the past, the statistics was used by rulers.

The application of statistics was very limited but rulers and kings needed information about lands, agriculture, commerce, population of their states to assess their military potential, their wealth, taxation and other aspects of government.

Basic forms of statistics have been used since the beginning of civilization. Early empires often collected censuses of the population or recorded the trade in various commodities.

The Roman Empire was one of the first states to extensively gather data on the size of the empire's population, geographical area and wealth.

During the 20th century several statistician are active in developing new methods, theories and application of statistics.

Now these days the availability of electronics computers is certainly a major factor in the modern development of statistics.

History of StatisticsTimeline

Statisticians

Sir William Petty A 17th-century economist who used early Statistical methods to analyze demographic data.

Carl Friedrich Gauss, -mathematician who developed the method of least square. 1809

Ronald Fisher"A genius who almost single-handedly created the foundations for modern statistical science", James Lind -carried out the first ever clinical trial in 1747, in an effort to find a treatment for scurvy.

What is Statistics

Definition A collection of methods for planning experiments,

obtaining data, and then then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.

.

Collection of data refers to the process of obtaining information.

Organization of data refers to the ascertaining manner of presenting the data into tables, graphs, or charts so that logical and statistical conclusions can be drawn from the collected measurements.

Analysis of data refers to the process of extracting from the given data relevant information from which numerical description can be formulated.

Interpretation of data refers to the task of drawing conclusions from the analyzed data.

Branches of Statistics

Descriptive

Inferential

Branches OF Statistics

Descriptive Statistics

The branch of statistics that focuses on collecting, summarizing, and presenting a set of data

Measure of Central Tendency Mean Median Mode

The average age of all students that are appeared in National aptitude test 2015

The average result of Fbise SSc examination If we had the results of 100 pieces of students

course work , we may be interested in the overall performance of those students

Inferential Statistics

The branch of Statistics that analyzes sample data to draw conclusions about a population.

For instance, suppose a survey group wants to know the prevailing sentiments among Filipino people on a certain issue. Asking every Filipino to answer a questionnaire would be impossible. It is expensive, time-consuming, and impractical. Instead, a small part of the entire population is scientifically chosen. The data gathered from this group is used to draw a general opinion of the entire population.

Suppose a researcher is interested to check the competence of Universities in Punjab it might, definitely impossible for him to survey the all universities of Punjab so he chose some universities technically or scientifically. The data gather from this group is used to make general conclusion

Terms Of Statistics

Population The complete collection of all elements (scores,

people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied

Population refers to the totality of all the elements or persons for which one has an interest at a particular time.

A researcher may associate a population to the ages of graduating students,, the I.Q. scores of the employees, the income of single parent, and so on. The usual notation for population is N.

We are the population of Masters of Education Subject Student of the Furc university are the population of

the reasearcher who was intrested to know the sentiments of students

Censusthe collection of data from every member of the population.

Sample a sub-collection of elements drawn from a population.

• To be continued

Sample is a part of population determined by sampling procedures. It is usually denoted by n.

Sample data must be collected in an appropriate way, such as through a process of random selection.

If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistical operation can be held properly

Social sciences

Education

Ma education

Ms education

psychology

MSc Psychology

Parameter

A numerical measurement describing some characteristic of a population

population parameter

Statistic

A numerical measurement describing some characteristic of a sample Sample

Statistics

variable

It is a specific factor, property, or characteristic of a population or a sample which differentiates a sample or group of samples from another group. For example, the score obtained from a coeducation

class may differ by gender. Hence, gender is considered variable. In a catholic congregation, religion cannot be considered a variable since every member the population is Catholic.

Discrete variable is a variable that can be obtained by counting.

Examples: the number of chairs and fans in our class room

Continues variable is a variable that can be obtained by measuring objects or attributes.

Examples: the weight of students, the temperature in a city over a period of time, the area of classrooms.

Variables are properties of characteristics of people or tings that vary in characteristics, quality or magnitude from person to person or object to object Demographic characteristics Personality traits Communication styles or competencies constructs

Independent variable Dependent Variable Confounding variable Mediating Variable Continues variable Discrete Variable

Data and Variable

Data are often discussed in terms of variable Any characteristics that vary from one member of

population to another height, Bp, I Q level

Data

Observations (such as measurements, genders, survey responses) that have been collected.

Forms Of Data

Quantitative Data

Qualitative Data

Qualitative (or categorical or attribute) data

It can be separated into different categories that are distinguished by some nonnumeric characteristics.

Example: genders (male/female) of professional athletes. yes/no

Quantitative data

Quantitative data refers to numerical information obtained from counting or measuring that which be manipulated by any fundamental operation.

Examples: Age, I.Q. scores, height, weight,

income,Expenses,Gdp Weight of all students of nursery class No of students in Ma Education class How many Applicants applied to FURC in fall

2014?

Working with Quantitative Data

Quantitative data can further be distinguished between Discrete and Continuous types.

Discrete Data result when the number of possible, values is

either a finite number or a ‘countable’ number of possible values.0, 1, 2, 3, . . .

Example: The number of eggs that hens lay The number of subjects in 2nd semester

Continuous (numerical) Data result from infinitely many

possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps.

Example: The amount of milk that a cow produces; e.g. 2.343115 gallons per day.

Qualitative:•He is brown and black•He has long hair•He has lots of energyQuantitative:•Discrete:

•He has 4 legs•He has 2 brothers

•Continuous:•He weighs 25.5 kg•He is 565 mm tall

Level Of Measurement

Another way to classify data is to use levels of measurement

Nominal Level of Measurement It characterized by data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme (such as low to high)Example: survey responses yes, no, undecided

Ordinal level of measurement It involves data that may be arranged in some order, but differences between data values either cannot be determined or are meaningless

Example: Course grades A, B, C, D, or F

Interval level of measurement like the ordinal level, with the additional property

that the difference between any two data values is meaningful. However, there is no natural zero starting point (where none of the quantity is present)Example: Years 1000, 2000, 1776

Ratio level of measurementThe interval level modified to include the natural zero starting point (where zero indicates that none of the quantity is present). For values at this level, differences and ratios are meaningful.

Example: Prices of college textbooks ($0 represents no cost)

Summary - Levels of Measurement

Nominal - categories only

Ordinal - categories with some order

Interval - differences but no natural starting point(zero point)

Ratio - differences and a natural starting point( no zero point)

Questions

What is the Difference between four level of Measurement?

What is parameter and Statistics? Which writer first use term Statistics in His drama? Name of the staticistcians that are mentioned in

presentation?

Presented ByAyesha sarfaraz and Sidra Afzal