The safzakabdul’s Podcast
New podcast weblogBAM 212 BUSINESS STATISTICS Statistics is simply a science of data. It is a methodology for collection; organizing; summarizing, presenting analyzing interpreting and drawing conclusions or inferences from given data. Furthermore, the word statistics is used rather curiously in two senses plural and singular. In the plural sense, it refers to a set of figures or data themselves; example unemployment statistics, infant death statistics among others. In the singular sense, statistics is defined as a discipline of study. Hence, statistics is a technique of gaining information from numerical and categorical data. Types / Branches of Statistics There are two (2) types/branches of statistics namely; 1. Descriptive statistics 2. Inferential statistics Descriptive statistics is a method of organizing, presenting, computing and summarizing information from data. Descriptive statistics includes the construction of graphs, charts and tables and calculation of various descriptive measures such as averages, measures of variation, and percentiles. However, this branch of statistics does not allow one to draw any conclusion or make any inferences about the data. Inferential statistics is the method of using information from a sample to draw conclusions about the population. Inferential statistics include methods like point estimation, interval estimation and hypothesis testing which are essentially based on probability theory. Importance of statistics 1. The knowledge of statistics enable us to condense and summarize voluminous data into more meaningful, presentable, and understandable. This is because the data in its raw form will not allow any inferences to be drawn. 2. Classification and comparison of data is easily done with the aid of statistical knowledge. Raw data when arranged based on certain characteristics will enable the investigation to make comparison between variables. 3. Statistical techniques such as correlation and regression helps in determining the functional relationship between or among variable for example a Geographer may use the knowledge of such technique to examine the relationship between rainfall and agricultural productivity. 4. Similarly it could be used by an educationist to find out the relationship between students’ performance and their parents socio-economic background. 5. It also enables an investigator to predict the future trends based on the previous data. For example, a businessman can predict the future sales of a particular product based on the previous sales record. Nature of Statistical Data Data simply mean information, numerical facts, observations or evidence. Statistical data to be used in any research generally comes in two major forms namely: a) Primary and b) Secondary Data Primary Data are data collected by or on behalf of the person or people who are going to make use of the data. It is the data collected specifically for a purpose and used for the purpose for which they are collected. Examples of Primary data are: (i) Heights and weights of students collected to determine their nutritional well-being. (ii) The population of Primary school pupils in the states of the country to allow the Federal Government plan for the primary education. The various methods of collecting primary data include surveys, interview, observation, questionnaire and experiments. Primary data could be very expensive to collect when the elements of the study sample are widely scattered and when the items of equipment for data collection, as in many experiments, are capital intensive. However errors can be minimized when collecting primary data since the researcher can always take adequate precaution in collecting primary data. Secondary Data This is the data that is used by a person or people other than the person or people by whom or for whom the data was collected. These are the data collected for some other purpose, frequently for administrative reasons, and used for the purpose for which they were not collected. Secondary data are always collected from published sources, like textbooks, journals, Newspapers, magazines, and gazette. Examples of secondary data include: (i) Accident fatalities on a particular road over a period of time collected from the Police or Road safety corps. (ii) Dietary requirements of various age groups collected from a nutrition textbook. (iii) Age distribution in Nigeria collected from the publications of the National Population Census. Methods of Data Collection 1. Surveys In this unit, you have learned that secondary data are already available; hence they must be collected when there is the need to use them. The collection of primary data involves survey or inquiry of one type or the other. Some surveys can be limited in the sense that they can be carried out with a few minutes of observation. Others can be detailed. When surveys are detailed, information from the surveys are more acceptable and valued than when they are limited. Examples of surveys are: (i) Government Survey (ii) Market research surveys - carried out for one particular client and not published in any form. (iii) Research surveys - carried out by academicians and published in journals 2. Observations This is one of the methods of collecting primary data. It can be used to know the use a particular facility is put. It can be used to study the behaviors of people in a work place. 3. Interviewing This is a conversation with a purpose. There can be formal and informal interviews. Informally everybody uses interviews to obtain information. The formal interview is also initiated by the interviewer who approaches the person he is interested in interviewing. The interviewer therefore arranges the venue, and the time, and prepares the questions to be asked. The interviewer also secures the means of recording the responses. 4. Questionnaire This is a list of questions drawn in such a way that the questions are related to the objectives of the study being conducted, and the responses to the question will be analyzed to provide solutions to the problems we attempt to solve in the study. There are two types of questionnaire namely: (i) Structured or fixed-response questionnaire: (ii) Unstructured or open ended questionnaire The structured questionnaire consists of a list of questions drawn on the study being conducted. Each question is accompanied by alternative answers from which the respondent picks appropriate answer or answers. An example of a structured question is this: What is your monthly salary? • Below N7500 • N7500 - N10,000 Unstructured questionnaire is a list of questions drawn on the study on which information is required. The questions are not accompanied by alternative answers as in the structured questionnaire. The respondents are free to provide their own responses. Example of a question in an unstructured questionnaire is ”What is your monthly salary?” Unstructured questionnaire are not difficult to construct since no question is accompanied by alternative answers. POPULATION AND SAMPLE Population is the entire aggregation of cases that meet the designated set of criteria. It includes a complete set of persons or objects that possess same characteristics that is of interest to the researcher. The population usually is described as Target population which is also called the universe, is composed of entire group of people or objects to which the researcher wishes to generalize the findings of a study, target population consists of people or things that meet the designated set of criteria of interest to researcher. Population is not restricted to human subjects. A population might consist of all the hospital records on file or all blood samples. The researcher usually samples from an available group, called the accessible population or study population. The researcher needs to identify the accessible population from which generalization of the study finding can be drawn. Sample and Sampling The sample represents the population of those critical characteristics you plan to study. In other words, if the sample is representative of the population you can say that what you have found out about the sample is true of the population. The term representative means that sample subjects are not selected haphazardly, but deliberately so that every element in the population has an equal chance of being selected for the study. The process of selecting a fraction of the sampling unit of your target population for inclusion in your study is called sampling TYPES OF SAMPLING Sampling plans can be grouped under two categories- Probability sampling and Non-probability sampling. Probability sampling uses a technique by which the researcher ensures the probability, that each element of population will be included in the sample. That is each element has an equal or known chance of being included. It utilizes some form of random selection because of which greater confidence can be placed in the representativeness of probability samples. Non-probability samples use non-random methods i.e. there is bias in the selection. There is no assurance that every element has a chance of being included or, in other words the researcher cannot estimate the probability that each element will be included in the sample. Kind of probability samples are: Simple Random Sample, Systematic Sample, Stratified Sample and Cluster Sample. The examples of Non-probability sampling are: Purposive Sampling, Convenience Sampling (or accidental sampling) and quota sampling.
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Sunday Aug 25, 2024