Scientist to find their results they use statistics to analyze. This helps them understand their research to help them conclude by confirming or rejecting a hypothesis if you are wondering how researches get a statistical tutorial to help in their scientific method.

**Research data**

Often during their research, scientist produce data and information than they need. This data is called the raw data and to analyze this data scientists such arrange and summarize the raw data into manageable chunks to form a data set. Depending on the research, your statistics can change and if you have any doubts, it is much easier to cross-check to help you get the best approach or conclusion. A good statistician help will ensure that the raw data can help you give a better view of what is going on and the reasons that can influence the conclusion.

**Central tendency and Normal distribution**

This part of statistics enables you to understand how data sets are related. In normal distribution, a frequency curve makes sure to get the middle number to assume the experiment on. The mean median and mode help measure the central tendency to help you in your statistical research. Central tendency helps you give a good idea about the nature of the mean, which combines measurements oh how the distribution is received by using the variance, standard deviation, standard error of the mean.

**Hypothesis Testing**

This involves a lot more than making use of statistical formulas but getting used of statistical software which involves understanding the relationship between probability and statistics, understanding descriptive statistics and inferential statistics, knowledge to understand scientific method. Statistics inference help you draw a conclusion, which is a critical part to help you with the test. This helps create an alternative hypothesis to test against the null hypothesis.

**Reliability and experimental error**

Statistical test makes use of data from samples to generalize the result to the population. Errors in the research is one of the crucial parts of testing as it helps you produce reliable information. If this is testable, there re many possibilities for the test to go wrong. This gets you experimental errors which can be broken down to calculate true positives and false positives. This margin of error is related to confidence intervals, which estimate the effect size and sample size, which needs generalization.

**Statistical tests**

Some commonly used statistical test methods used by researchers are:

- Relationship between variable
- Predictions by using regression analysis like linear regression, multiple regression, factor analysis, meta-analysis.
- Testing hypothesis statistically by using Independent One sample T-test, two-sample test, dependent test for paired samples.
- Comparing more than two groups using ANOVA analysis of variance.

Non-parametric statistics like coefficient.