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Statistics is a science that deals with studying and developing methods for analyzing, correlating, interpreting, and presenting data. There are two main ideas in the field of statistics which are variation and uncertainty. One major area of study in statistics is probability, a mathematical language used to discuss uncertain events. Statistics is divided into two main branches. The branches are;
- Descriptive statistics – This branch of statistics deals with data collection and presentation. In statistical analysis, descriptive statistics comes first. However, it is essential to note that it is not as simple as it sounds because one must choose a focus group and know how to design experiments.
- Inferential statistics - In inferential statistics, one has to draw the right conclusions from statistical analysis, which is done through descriptive statistics. In general, many future predictions about a population are done on a small sample. By designing good experiments, a researcher can come up with conclusions that are relevant to the study. When concluding statistics, one has to be careful not to draw biased conclusions.
Both descriptive and inferential statistics go hand in hand and therefore it’s not possible for one to exist without the other.
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Importance of statistics in research
- Statistics inform methods on data collection – Through statistics, one can know which method of data collection is suitable for the study or research they are carrying out. There are many methods of data collection, and therefore you need to have an idea of the method that best suits the type of study you are carrying out.
- Statistics is used to support or negate hypotheses – Through statistics, there is an objective way of showing whether the data supports or does not support certain research questions. The evidence collected in supporting or not supporting a hypothesis solely remains on the conclusions drawn by statistics.
- Helps in removing uncertainty and errors in data – Data cannot always be clean. It is sometimes messy and incomplete. Therefore through statistics, one can know where data is not correct and where it is not complete.
- Help in aiding integration and communication of datasets – Having used the right statistical tests, objective conclusions can easily be interpreted. Statistical tests help people accurately interpret the dataset.
- Multivariate statistics and modeling - It would be impossible to tease the different effects that influence the dependent variable without statistics. What is more, it would be impossible to identify the factors working to produce a compounded impact on dependent variables.