INTRODUCTIN SOME BASIC CONCEPTS

Statics is a field of study concerned with1. collection, organization, summarization

presenting and analysis of data2.Drawing of inferences about a body of data

when only part of data is observed.

DATA The raw material of statics is data.We may define data as raw figures. Figures result

from the process of counting or from taking a measurement .

For example;When a hospital administrator cants the number of

patients (counting)When a nurse weights a patient (measure ment)

SOURCES OF DATAWe search for suitable data to serve as the

raw material for our investigation.Such data are available from one more of the

following sources.1.ROUTINELY KEPT RECORDS.2.EXTERNAL SOURCES.3.SURVEYS.4.EXPERIMENTS.

VARIABLE• It is characteristics that takes on different

values in different persons, places or things.• For exampleHeart beat rateThe heights of adult males The Wight of preschool children

TYPES OF VARIAPLESQUANTITATIVE VARIABLES

It can be measured in the usual sense.

For exampleo The heights of adult

maleso The weights of

preschool children

QUALITATIVE VARIABLES

Many characteristics are not capable of being measured.

For exampleo Classification of people into

socio-economic groups, social classes based on income education, etc.

TYPES OF QUANTITATIVE VARIABLES

A discrete variableis characterized by gaps

or interruptions in the values that it can assume.

For exampleThe number of daily

admissions to a general hospital.

A continuous variableCan assume any value

within a specified relevant interval of values assumed by variable.

For exampleHeight,Weight,Skull circumference.

TYPES OF QUALITATIVE VARIABLES

NOMINALAs the name implies it

consists of naming or classifies into various mutually exclusive.

For exampleMale-femaleSick-wellMarried-single-

divorced.

ORDINALWhen ever qualitative

observation ranked or ordered according to some criterion.

For exampleBlood pressure (high-

good-low)Grades (excellent-

v.good-good-fail)

POPULATIONIt is the largest collection of values of a

random variable for which we have an interest at a particular time.

For exampleThe weights of all the children enrolled in a

certain elementary school.Populations may be finite infinite.

SAMPLEIt is apart of a population .For exampleThe weights of only a fraction of these

children.

PARAMETER AND STATISTICParameter.A descriptive measure computed from the

data of population. (Quantity calculated from population)

A descriptive measure computed from the data of a sample (Quantity calculated from the sample)

SAMPLING PROCEDURESampling is the process by which a relatively

small number of individuals or measures of individual, objects or events is selected and analyzed in order to find out something about the entire population from which it selected.

For steps are involved in the process of sampling. Define the population (finite or an-finite)Listing the population (sample frame)Selecting a representative sample (sampling)Obtaining an adequate sample (sample size)

SAMPLING METHODS

Sampling methods

Probability samplingNon-Probability sampling

A)PROBABILITY SAMPLINGEvery unit of population has one fixed

probability of being included in the sample, this also called random sampling.

In random sampling every sample of given size in the accessible population has an equal chance of being selected.

METHODS OF RANDOM SAMPLING

Random sampling

Simple or unrestricted

random sampling

Systematic sampling

Stratified

random samplin

g

B)NON-PROBABILITY SAMPLING

It is a biased sampling used when there is interest in selecting sample because the focus is on in-depth in formation and when the sampling frame absent.

METHODS OF NON-PROBABILITIY

Non- probability sampling

Convenience sampling

Purposive sampling

Quota sampling

Snowballing sampling

ERRORS OF SAMPLINGWhen we take a sample, our results will not

exactly equal the correct result for the whole population. That is, our result will be subject to errors.

Sampling error is the discrepancy between the characteristics of the population and the characteristics of the sample

ERRORS IN SAMPLING ERRORS IN

SAMPLING

Sampling error (random error)

Non-sampling error (bias)