FUNDAMENTAL CONCEPTS OF STATISTICS (Part 1 - The Nature of Statistics)

Indirect or Questionnaire Method.

This is one of the easiest methods of data gathering. It takes time to prepare because questionnaires need to be attractive. The content of a typical questionnaire, directions included, must be precise, clear and self-explanatory. Illustrations and pictures may be used to add clarity and attractiveness.

Direct or Interview Method.

This is one of the most effective methods of collecting original data. To obtain accurate responses, well-trained interviewers may do the interview. The interviewers can be of great help to the respondents in answering questions that the respondents cannot understand. It provides consistent and more precise information; however, it can be time-consuming, expensive and has limited field coverage.

Experiment Method.

This method is applied to collect or gather data if the investigator wants to control the factors affecting the variable being studied. An example is when the researcher aims to determine the different factors affecting the academic performance of the students such as methods or approaches used in teaching, etc. Experiments are conducted to determine the cause-and-effect relationship of certain phenomena under controlled conditions.

Telephone Interview

This method is employed if the questions to be asked are brief and few. An example is the check made on listeners to certain radio programs like asking what program his radio is turned on to. This method is used to find the most popular TV or radio programs.

Observation Method.

This method is utilized to gather data regarding attitudes, behavior, values and cultural patterns of the samples under investigation.

Registration Method.

Through this method, the respondents provide information in compliance with certain laws, policies, rules, regulations, decrees or standard practices. Data which can be collected by the registration method are as follows: marriage contracts, birth certificates, motor registrations, license of firearms, registration of corporations, real estates, voters, etc.

Inferential Statistics

demands a higher order of critical judgment and mathematical methods. It aims to give information about large groups of data without dealing with each element of these groups. It pertains to the methods dealing with making inference, estimates or prediction about a large set of data using the information gathered.

parameter

descriptive measure of the population

class average of examination, range of student scores, average salary, means of managerial satisfaction, and average return of investment.

examples of descriptive stat

Statistical knowledge

helps us use the proper methods to collect the data, employ correct analyses, and effectively present the results. It is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions.

Statistics

is a branch of mathematics which deals with the collection, presentation, analysis, and interpretation (CPAI) of numerical data which may be used for prediction or verification of relationships among variables.

Ratio Scale

is an interval scale modified to include inherent zero starting point.

Descriptive Statistics

is concerned with the gathering, classification and presentation of data and the collection of summarizing values to describe the group characteristics of the data.

Sampling

is the process or technique of drawing the sample from the population.

in economics

it determines, trends, helps financial analysts make investment decisions and determines the potential of an investment including inventory turn-over ratio of cash flow to total assets; the quick ratio which is the ratio of the difference between current assets and inventory values to current liabilities; return on assets before taxes; and controls of the quality of goods produced and many others.

Data gathering or collection

may be done through interview, questionnaires, tests, observation, registration, and experiments.

raw data

measurements that are collected from the original information. these data may be treated by statistical methods that are used to describe, to relate, or associate, and make inference, depending on the nature or purpose of the research problems on hand.

percentage, measures of central tendency and location; of variability or dispersion; of skewness and kurtosis

most used summarizing values to describe group characteristics of data

Ordinal Scale (Ranked)

not only classify items, but also give the order or ranks of classes, items or objects. The differences between data values either cannot be determined or meaningless.

hypothesis using the z-test, t-test, simple linear correlation, analysis of variance (ANOVA), chi-square, regression, and time series analysis

Commonly used inferential statistical tools or techniques are

Statistics

Generally, the term means numerical observation of any kind.

Statistics

A quantity calculated from the observations in a sample is called a _________ (sample mean, sample median, sample mode, sample variance, and sample standard deviation). Usually denoted by small English letters.

Universe

A universe is the set of all the individuals or entities under consideration.

Variable

A variable is a characteristic of interest measurable on each individual of the universe. It is a quantity which may take on several different value

Survey

1. is limited to a particular area or locality.

Parameter

A numerical characteristic of a population is called a _______. _______ of a given population are constants or fixed for that population (population mean, population variance, population standard deviation, and population size). _______ are usually denoted by Greek letters and/or capital English letters

Descriptive and Inferential Statistics

The field of statistics may be divided into two categories:

Population

a. A population is the set of all possible values of a variable. b. A population is the set of all observations made on all objects under study for a given characteristic or variable.

Sample

a. A sample is a set of observations which constitute a part of a population. b. A sample is the representative part of the population selected for the purpose of making inference about the population

statistics as science

are evident in empirical studies. Among the contributions of statistics are it aids in decision making, summarizes or describes data, helps to forecast or predict future outcomes, aids in making inferences, and helps in comparisons or establishing relationships

Interval Scale

are numbers assigned to items not only to identify and rank the objects but also measure the degree of differences between any two classes. It may lack inherent zero starting point.

Discrete or discontinuous data

are those obtained by counting (number of days, number of students, etc.). Remarks: In Statistics, although some data are discrete, they may be treated as continuous. We may have this type of data, that is, the average number of children per family in a certain barangay is 3.4.

Continuous data

are those obtained by measurements (length of a room, weight of a stone, 4 meters, 15 pounds, etc.).

Dependent variables

are those variables where the existence of the first is influenced by the occurrence of the second variable.

Independent variables

are those variables where the occurrence of the first is not relative to the existence of the second variable (for example, the number of fishermen is independent of the number of deaths in a given province).

Qualitative variables

are those which change in quality. They are rankables (kindness, temperament, loyalty, truthfulness, etc.).

Quantitative variables

are those which change in quantity. They are measurables (intelligence, height, weight, size, length, etc.).

Greek letters

are used to represent parameters

ability to make decisions about parameters without having the complete census of the population

basis for inferential statistics is the

Census

considers the national boundaey of a country

Nominal Scale (Categorical)

consists only of names, labels or categories which are used merely for identification or classification purposes.

Analysis of data

pertains to the process of extracting from the given data relevant and noteworthy information and this uses statistical tools or techniques.

μ (mu)

population mean

σ (sigma

population standard deviation

σ2

population variance

Primary data

refer to information which are gathered directly from an original source, or which are based on direct or first-hand experience (autobiographies, diaries, interviews, etc.).

Secondary data

refer to information which are taken from published or unpublished data which are previously gathered by other individuals or agencies (published books, newspapers, biographies, business reports, etc.).

Interpretation of data

refers to the drawing of conclusions or inferences from the analyzed data. This may involve the formulation of forecast prediction about a large group based on the data collected from small or representative group.

Presentation of data

refers to the organization of data into tables, graphs, charts, or paragraphs. Hence, presentation of data may be tabular, graphical, or textual.

in education

statistical techniques and methods are used to get information on enrollment, finance, physical facilities, dropout rate, proficiency level and many others

in research

statistical tools are used to test differences, effectiveness, impact, relationship, or independence of some variables.

population

the conclusions on the important characteristics apply to a large set of data

sample

the subset or a representative group of the population is called the

statistical data

took the forms of figures or birth, death, tax returns, population, frequency of failures in schools, crop yield, etc.

Roman letter

used to denote a test statistic.

Management

uses statistics in decision making and in varied aspects such as organizational behavior, labor relations, human-resource allocation, performance assessment and evaluation for the improvement of personal relation.