Covariance and Correlation are two mathematical concepts which are quite commonly used in business statistics. Both of these two determine the relationship and measures the dependency between two random variables. Despite, some similarities between these two mathematical terms, they are different from each other. Correlation is when the change in one item may result in the change in another item. Correlation is considered as the best tool for for measuring and expressing the quantitative … [Read more...]

The terms responsibility and accountability are often used interchangeably by the people, due to some similarities like the flow of both of these two, is from bottom to top. Although, they are different in the sense that, in the case of responsibility, a person does what he/she is asked to do. On the other hand, in accountability, a person agrees to do, what he/she is supposed to do. The basic difference between responsibility and accountability is that the former is assumed whereas the … [Read more...]

In statistics, you have come across the terms, observation and inference, several times. Observation means an act of monitoring, something, i.e. objects, units, persons or anything else, by using senses. In this process, the observer stays at the place of the survey and observes the objects under consideration and notes down the observations himself. Conversely, Inference refers to the conclusion drawn based on the facts and evidence available, i.e. deductions are made as per the research … [Read more...]

Primary data is described as a data originally collected, in essence, the data gathered is afresh and for the first time. Surveys and Experiments are two important statistical techniques used in research and data collection. When the research type is experimental, experiments are considered as a major source of primary data. On the other end, surveys are performed when the research is descriptive in nature. While surveys collected data, provided by the informants, experiments test various … [Read more...]

People quite commonly use questionnaire and schedule interchangeably, due to much resemblance in their nature; however, there are many differences between these two. While a questionnaire is filled by the informants themselves, enumerators fill schedule on behalf of the respondent. The research process is incomplete without collection of data, which starts after identification of research problem and chalking out research design. The researcher should keep in mind that there are two types of … [Read more...]

Generation of the hypothesis is the beginning of a scientific process. It refers to a supposition, based on reasoning and evidence. The researcher examines it through observations and experiments, which then provides facts and forecast possible outcomes. The hypothesis can be inductive or deductive, simple or complex, null or alternative. While the null hypothesis is the hypothesis, which is to be actually tested, whereas alternative hypothesis gives an alternative to the null … [Read more...]

In statistics vocabulary, we often deal with the terms parameter and statistic, which play a vital role in the determination of the sample size. Parameter implies a summary description of the characteristics of the target population. On the other extreme, the statistic is a summary value of a small group of population i.e. sample. The parameter is drawn from the measurements of units in the population. As against this, the statistic is drawn from the measurement of the elements of the … [Read more...]

In statistic, the arithmetic mean is one of the ideal measures of central tendency. For a given set of observations, the arithmetic mean can be calculated by adding all the observations and dividing the value obtained by the number of observations. There are two types of mean, i.e. sample mean and population mean, which is often used in statistics and probability. The sample mean is mainly used to estimate the population mean when population mean is not known as they have the same expected … [Read more...]

Sampling error is one which occurs due to unrepresentativeness of the sample selected for observation. Conversely, non-sampling error is an error arise from human error, such as error in problem identification, method or procedure used, etc. An ideal research design seeks to control various types of error, but there are some potential sources which may affect it. In sampling theory, total error can be defined as the variation between the mean value of population parameter and the observed … [Read more...]

Data collection plays a very crucial role in the statistical analysis. In research, there are different methods used to gather information, all of which fall into two categories, i.e. primary data, and secondary data. As the name suggests, primary data is one which is collected for the first time by the researcher while secondary data is the data already collected or produced by others. There are many differences between primary and secondary data, which are discussed in this article. But the … [Read more...]