Independent vs Dependent variables- Definition, 10 Differences, Examples

Independent Variables The Independent variable is a type of variable used in experimental sciences, statistical modeling, and mathematical modeling which doesn’t depend on any other variables in the scope of the experiment. An independent variable can be manipulated in an experiment, which in turn affects the changes in the dependent variables. Mostly in mathematical equations, independent variables are denoted by ‘x’. Independent variables are also termed as “explanatory variables,” “manipulated variables,” or “controlled variables.” In a graph, the independent variable … Read more

Type I Error and Type II Error- Definition, 10 Differences, Examples

Image Source: AB Tasty. Type 1 error definition Type 1 error, in statistical hypothesis testing, is the error caused by rejecting a null hypothesis when it is true. Type 1 error is caused when the hypothesis that should have been accepted is rejected. Type I error is denoted by α (alpha) known as an error, also called the level of significance of the test. This type of error is a false negative error where the null hypothesis is rejected based … Read more

Chi-square Test- Definition, Formula, Uses, Table, Examples, Applications

What is a Chi-square test? A Chi-square test is performed to determine if there is a difference between the theoretical population parameter and the observed data. Chi-square test is a non-parametric test where the data is not assumed to be normally distributed but is distributed in a chi-square fashion. It allows the researcher to test factors like a number of factors like the goodness of fit, the significance of population variance, and the homogeneity or difference in population variance. This … Read more

Null hypothesis and alternative hypothesis with 9 differences

Null hypothesis definition The null hypothesis is a general statement that states that there is no relationship between two phenomenons under consideration or that there is no association between two groups. A hypothesis, in general, is an assumption that is yet to be proved with sufficient pieces of evidence. A null hypothesis thus is the hypothesis a researcher is trying to disprove. A null hypothesis is a hypothesis capable of being objectively verified, tested, and even rejected. If a study … Read more

Common mistakes in Proposal writing

Some of the mistakes are: Choosing a topic that is too large. Choosing a topic that is too complex for research at the level of the researcher. Not giving due consideration to the time factor. This factor is important because the research work is to be completed within the prescribed time period. Choosing research where materials are not easily accessible. Choosing research that is not researchable because the methodology of the study is not yet developed or outdated or incomplete. … Read more

Quantitative vs Qualitative Data- Definition, 13 Differences, Examples

Quantitative and Qualitative Data Definition Qualitative data is data concerned with descriptions, which can be observed but cannot be computed. On the contrary, quantitative data is the one that focuses on numbers and mathematical calculations and can be calculated and computed. So, for the collection and measurement of data, any of the two methods discussed above can be used. Although both have its merits and demerits, i.e. while qualitative data lacks reliability, quantitative data lacks a description. Both are used in conjunction … Read more

Z-test- definition, formula, examples, uses, z-test vs t-test

z-test definition z-test is a statistical tool used for the comparison or determination of the significance of several statistical measures, particularly the mean in a sample from a normally distributed population or between two independent samples. Like t-tests, z tests are also based on normal probability distribution. Z-test is the most commonly used statistical tool in research methodology, with it being used for studies where the sample size is large (n>30). In the case of the z-test, the variance is … Read more

P-value- definition, formula, table, finding p-value, significance

p-value definition The p-value or the calculated probability is the best probability to provide the smallest level of significance at which the null hypothesis is not true. It is the best-case scenario under which the test results will be the same as the results actually observed under the condition that the null hypothesis is correct.  A small p-value indicates the result is possible but not very likely under the null hypothesis. P-value works as an alternate for the rejections point … Read more

ANOVA- definition, one-way, two-way, table, examples, uses

ANOVA Definition ANOVA (Analysis of Variance) is a statistical tool to test the homogeneity of different groups based on their differences. ANOVA is the method of analyzing the variance in a set of data and dividing the variance into groups according to the sources of those variations. ANOVA is based on the principle that the total amount of differences in a set of data can be divided into two types, the amount that can be attributed to chance and the … Read more

Questionnaire- Types, Format, Questions

A questionnaire is defined as a document containing questions and other types of items designed to solicit information appropriate for analysis. The questionnaire may be regarded as a form of an interview on paper. Procedure for the construction of a questionnaire follows a pattern similar to that of the interview schedule. However, because the questionnaire is impersonal it is all the more important to take care of its construction. Since there is no interviewer to explain ambiguities or to check … Read more