Stratified sampling: Definition, Allocation rules with advantages and disadvantages

stratified sampling

Stratified sampling is a sampling plan in which we divide the population into several non-overlapping strata and select a random sample from each stratum in such a way that units within the strata are homogeneous but between strata they are heterogeneous. Stratum is a group of elements where all the units of elements “within the … Read more

Simple Random Sampling: Applications, Advantages and Disadvantages

simple random sampling

Simple random sampling is the easiest and most popular method of probability sampling. To perform simple random sampling, all a researcher must do is ensure that all members of the population are included in a master list, and that subjects are then selected randomly from this master list. While simple random sampling creates samples that are … Read more

Normality checking of a data set using spss

normality check using spss

In data analysis, normality checking of data set is very important. Because normally distributed data produces more accurate result. Basically we check the normality using histogram. If the shape of the histogram is bell shaped then the data set follow the normal distribution. We also use the normality table including kolmogrov-smirnov test and shapiro-wilk test … Read more

Bivariate analysis using spss (data analysis part-10)

bivariate analysis

Bivariate analysis is a statistical analysis which deals with two variables and find the relationship between the variables. We can perform bivariate analysis using SPSS, Stata and other statistical software very easily. Bivariate Analysis What is bivariate analysis? Bivariate analysis is the analysis of two random variable and find their association. The casualty and association … Read more

Univariate Analysis using SPSS

Univariate analysis in SPSS

Three different types of procedures can be used to analyze data in statistics. These include univariate, bivariate, and multivariate analysis. The number of variables and the type of data determine which data analysis method is used. Additionally, we have to consider the objectives of the statistical analysis. We can easily conduct univariate analysis using SPSS, … Read more

Non probability sampling methods with application, Pros and Cons

non probability sampling

Non-probability sampling is a method used in research where not every member of the population has a known or equal chance of being selected for the sample. Unlike probability sampling, where random selection ensures every individual has an equal opportunity to be included, non-probability sampling is more subjective, with researchers selecting participants based on convenience, … Read more

Probability sampling with application, Pros and Cons

Probability sampling is a research technique that gives every member of a population a known and non-zero chance of being selected in a sample. Researchers widely use this method in scientific studies, social sciences, market research, and environmental surveys to ensure accurate and representative data. In other words, Probability sampling is based on the concept … Read more

Sampling: Definition, Examples, Types, Application, Advantages and Disadvantages

sampling

Statistical sampling is a fundamental technique in statistics, used to make inferences about a population based on a smaller subset of data. It is widely used in research, quality control, market research, and many other fields. Instead of studying an entire population, which can be costly and time-consuming, sampling allows us to draw meaningful conclusions … Read more

Normal distribution: Definition, pdf, properties with applications

normal distribution

One of the most important tools in statistics is the normal distribution. It aids in determining specific data features and also serves as a foundation for employing other statistical techniques for decision-making. As a result, in this article, we look at the Normal distribution and its application in real life. In probability, the normal distribution … Read more

Regression Analysis with its types, Objectives and Applications

regression analysis

Regression analysis is a statistical technique that develops a relationship between explanatory (independent) variables and response (dependent) variables. It measures the dependence of one (dependent) variable on one or more other (independent) variables.  Linear regression Introduction of regression analysis The term regression was first introduced in the nineteenth century to describe a biological phenomenon, namely … Read more

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