What is a quantitative hypothesis?
Quantitative hypothesis contains a zero and alternative design, which is proven or refuted by statistical analysis. The process speculates that an independent variable affects a dependent variable and an experiment is carried out to see if there is a relationship between them. This type of hypothesis is given in numerical terms and has specific rules and limits. The zero hypothesis is either rejected or accepted as a result of statistical data collected during the experiments set. An example of a null hypothesis is "five additional hours of study time a week lead to a higher diameter of points for university students". The alternative hypothesis would probably say that "five more hours of study time do not increase the average of college students'. In order to refuse or accept the zero hypothesis Experimental data would have to be recorded for a specified period of time.
Most of the studies that have decided to abstractAC data on measurement of quantitative hypothesis based on statistical significance, which means there is a low possibility of error. In the event of a demonstration or refutation of the influence of the study time on the averages of university students, a control group would probably be tested. The behavior and environment of these groups are usually checked by scientists. The data would also be obtained from a group of students whose behavior and environment have not been controlled.
Since quantitative hypothesis and research study rely on numerical data, the results of experiment or surveys are transferred to mathematical values. For example, many market research studies use scales that assign every response to numeric value. The "Agree" answer may correspond to the "4" number, while the response "disagreement" may match the "2nd" number When any survey feedback is recorded and analyzed, each number is assigned a percentage based on the total number of answers.
Statistical analysis with timeThis is used to explore the results of the survey and experimental data. Whether quantitative hypothesis is rejected or accepted depends on the numerical outcome of the analysis. For example, if the average point diameter must be at least 3.5 to prove that the amount of time of study has a direct effect, the diameter would lead to a diameter of 3.45 to reject quantitative hypothesis.